Maintenance And Diagnostics For Refrigeration Systems

ABSTRACT

A system and a method are provided including a controller for a refrigeration or HVAC system having a compressor rack with at least one compressor. The controller communicates with a tracking module configured to diagnose health of a compressor in the compressor rack. In response to rated performance data for the compressor being unavailable, the tracking module is configured to generate baseline data for the compressor and to diagnose health of the compressor by comparing operational data of the compressor to the baseline data for the compressor. In response to the rated performance data for the compressor being available, the tracking module is configured to diagnose health of the compressor by comparing the operational data of the compressor to the rated performance data for the compressor.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/197,169, filed on Jun. 29, 2016, which claims the benefit of U.S.Provisional Application No. 62/186,813, filed on Jun. 30, 2015. Theentire disclosures of the applications referenced above are incorporatedherein by reference.

FIELD

The present disclosure relates to refrigeration systems and, moreparticularly, to maintenance and diagnostics for refrigeration systems.

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventor(s), to the extent it is described in thisbackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

Refrigeration systems are an essential part of many commercial buildingand dwellings. For example, food retailers may rely on refrigerationsystems to ensure the quality and safety of food products. Many otherbusinesses may have products or materials that must be refrigerated ormaintained at a lowered temperature. HVAC systems allow people to remaincomfortable where they shop, work or live.

Refrigeration system operation, however, can represent a significantportion of a business' operating costs. As such, it may be beneficialfor refrigeration system users to closely monitor the performance andenergy consumption of the refrigeration systems to detect and diagnoseany performance issues so that maintenance can be performed to maximizeefficiency and reduce operational costs. Generally speaking, users maylack the expertise to accurately analyze system performance and detectand diagnose any performance issues.

SUMMARY

This section provides a general summary of the disclosure, and is not acomprehensive disclosure of its full scope or all of its features.

A system is provided and includes a system controller for arefrigeration or HVAC system having a compressor rack with at least onecompressor and a condensing unit with at least one condenser fan, thesystem controller monitoring operation of the refrigeration or HVACsystem. A rack controller is in communication with the systemcontroller, the rack controller monitoring and controlling operation ofthe compressor rack and determining compressor rack power consumptiondata. A condensing unit controller in communication with the systemcontroller, the condensing unit controller monitoring and controllingoperation of the condensing unit and determining condensing unit powerconsumption data. The system controller receives the compressor rackpower consumption data and the condensing unit power consumption data,determines a total power consumption of the refrigeration or HVAC systembased on the compressor rack power consumption data and the condensingunit power consumption data, determines at least one of a predictedpower consumption and a benchmark power consumption for therefrigeration system, compares the total power consumption with at leastone of the predicted power consumption and the benchmark powerconsumption, and generates a health indicator score based on thecomparison.

In other features, the system controller can receive performancecoefficients for the refrigeration or HVAC system and determine thepredicted power consumption based on the performance coefficients and onoperational data for the refrigeration or HVAC system.

In other features, the system controller can monitor power consumptiondata of the refrigeration or HVAC system over an initialization periodand determined the benchmark power consumption based on the monitoredpower consumption data for the initialization period.

A method is provided and includes monitoring, with a system controller,operation of a refrigeration or HVAC system having a compressor rackwith at least one compressor and a condensing unit with at least onecondenser fan. The method also includes monitoring and controller, witha rack controller in communication with the system controller, operationof the compressor. The method also includes determining, with the rackcontroller, compressor rack power consumption data for the compressorrack. The method also includes monitoring and controller, with acondensing unit controller in communication with the system controller,operation of the condensing unit. The method also includes determining,with the condensing unit controller, power consumption data for thecondensing unit. The method also includes receiving, with the systemcontroller, the compressor rack power consumption data and thecondensing unit power consumption data. The method also includesdetermining, with the system controller, a total power consumption ofthe refrigeration or HVAC system based on the compressor rack powerconsumption data and the condensing unit power consumption data. Themethod also includes determining, with the system controller, at leastone of a predicted power consumption and a benchmark power consumptionfor the refrigeration system. The method also includes comparing, withthe system controller, the total power consumption with at least one ofthe predicted power consumption and the benchmark power consumption. Themethod also includes generating, with the system controller, a healthindicator score based on the comparison.

In other features, the method also includes receiving, with the systemcontroller, performance coefficients for the refrigeration or HVACsystem and determining, with the system controller, the predicted powerconsumption based on the performance coefficients and on operationaldata for the refrigeration or HVAC system.

In other features, the method also includes monitoring, with the systemcontroller, power consumption data of the refrigeration or HVAC systemover an initialization period and determining, with the systemcontroller, the benchmark power consumption based on the monitored powerconsumption data for the initialization period.

Another system is provided and includes a system controller for arefrigeration or HVAC system having a compressor rack with at least onecompressor, the system controller monitoring and controlling operationof the refrigeration or HVAC system. A rack controller is incommunication with the system controller, the rack controller monitoringand controlling operation of the compressor rack. The system controllerdetermines a flood-back discharge temperature corresponding to aflood-back condition, receives an actual discharge temperatureassociated with the compressor rack, compares the actual dischargetemperature with the flood-back discharge temperature, and generates anotification to the rack controller based on the comparison.

In other features, the system controller generates the notification whena difference between the flood-back discharge temperature and the actualdischarge temperature is less than a predetermined threshold.

In other features, the rack controller implements a bump start operationafter receiving the notification.

In other features, the rack controller activates crank case heatersafter receiving the notification.

Another method is provided and includes monitoring and controlling, witha system controller, a refrigeration or HVAC system having a compressorrack with at least one compressor. The method also includes monitoringand controlling, with a rack controller, operation of the compressorrack. The method also includes determining, with the system controller,a flood-back discharge temperature corresponding to a flood-backcondition. The method also includes receiving, with the systemcontroller, an actual discharge temperature associated with thecompressor rack. The method also includes comparing, with the systemcontroller, the actual discharge temperature with the flood-backdischarge temperature. The method also includes generating, with thesystem controller, a notification to the rack controller based on thecomparison.

In other features, the method can also include generating, with thesystem controller, the notification when a difference between theflood-back discharge temperature and the actual discharge temperature isless than a predetermined threshold.

In other features, the method can also include implementing, with therack controller, a bump start operation after receiving thenotification.

In other features, the method can also include activating, with the rackcontroller, crank case heaters after receiving the notification.

Another system is provided and includes a system controller for arefrigeration or HVAC system having a compressor rack with at least onecompressor and a condensing unit with at least one condenser fan, thesystem controller monitoring and controlling operation of therefrigeration or HVAC system. A rack controller is in communication withthe system controller, the rack controller monitoring and controllingoperation of the compressor rack. A condensing unit controller incommunication with the system controller, the condensing unit controllermonitoring and controlling operation of the condensing unit. The systemcontroller receives forecast weather data for a future time period,determines a predicted refrigeration system capacity needed for thefuture time period based on the forecast weather data, compares thepredicted refrigeration system capacity with a predetermined capacitythreshold, and generates an alert when the predicted refrigerationsystem capacity is greater than the predetermined capacity threshold.

In other features, the system controller modifies operation of therefrigeration system prior to the future time period to reduce acapacity of the refrigeration system during the future time period.

Another method is provided and includes monitoring and controlling, witha system controller, operation of a refrigeration or HVAC system havinga compressor rack with at least one compressor and a condensing unitwith at least one condenser fan. The method also includes monitoring andcontroller, with a rack controller in communication with the systemcontroller, operation of the compressor. The method also includesmonitoring and controller, with a condensing unit controller incommunication with the system controller, operation of the condensingunit. The method also includes receiving, with the system controller,forecast weather data for a future time period. The method also includesdetermining, with the system controller, a predicted refrigerationsystem capacity needed for the future time period based on the forecastweather data. The method also includes comparing, with the systemcontroller, the predicted refrigeration system capacity with apredetermined capacity threshold. The method also includes generating,with the system controller, an alert when the predicted refrigerationsystem capacity is greater than the predetermined capacity threshold.

In other features, the method can also include modifying, with thesystem controller, operation of the refrigeration system prior to thefuture time period to reduce capacity of the refrigeration system duringthe future time period.

Another system is provided and includes a system controller for arefrigeration or HVAC system having a compressor rack with at least onecompressor and a condensing unit with at least one condenser fan. A rackcontroller for the compressor rack, the rack controller being incommunication with the system controller. A condensing unit controllerfor the condensing unit, the condensing unit controller being incommunication with the system controller. The system controller receivescomponent identification information identifying components of thecompressor rack and the condensing unit, retrieves component informationincluding at least one of component specification information, componentcapacity information, and component capability information, based on thecomponent identification information, and performs setup operationsbased on the component information.

In other features, the controller transmits first data including one ormore of the component identification information and the componentinformation to a remote device, receives second data from the remotedevice for controlling one or more of the components of the compressorrack and the condensing unit based on the first data sent to the remotedevice, and controls the one or more of the components of the compressorrack and the condensing unit based on the second data received from theremote device.

In other features, the controller transmits one or more of the componentidentification information and the component information to a remotedevice for diagnosing one or more of the components of the compressorrack and the condensing unit and scheduling service for the one or moreof the components of the compressor rack and the condensing unit fromthe remote device.

Another method is provided and includes receiving, with a systemcontroller, component identification information identifying componentsof a compressor rack and a condensing unit of a refrigeration or HVACsystem, the compressor rack having at least one compressor and anassociated rack controller and the condensing unit having at least onecondenser fan and an associated condensing unit controller. The methodalso includes retrieving, with the system controller, componentinformation including at least one of component specificationinformation, component capacity information, and component capabilityinformation, based on the component identification information. Themethod also includes performing, with the system controller, setupoperations for the refrigeration or HVAC system based on the componentinformation.

In other features, the method further includes transmitting, with thecontroller, first data including one or more of the componentidentification information and the component information to a remotedevice. The method further includes receiving, with the controller,second data from the remote device for controlling one or more of thecomponents of the compressor rack and the condensing unit based on thefirst data sent to the remote device. The method further includescontrolling, with the controller, the one or more of the components ofthe compressor rack and the condensing unit based on the second datareceived from the remote device.

In other features, the method further includes transmitting, with thecontroller, one or more of the component identification information andthe component information to a remote device for diagnosing one or moreof the components of the compressor rack and the condensing unit andscheduling service for the one or more of the components of thecompressor rack and the condensing unit from the remote device.

Another system is provided and includes a system controller for arefrigeration or HVAC system having a compressor rack with at least onecompressor and a condensing unit with at least one condenser fan. Thesystem also includes a rack controller for the compressor rack, the rackcontroller being in communication with the system controller. The systemalso includes a condensing unit controller for the condensing unit, thecondensing unit controller being in communication with the systemcontroller. The system controller receives component identificationinformation identifying components of the compressor rack and thecondensing unit, retrieves component information including at least oneof component specification information, component capacity information,and component capability information, based on the componentidentification information, and performs setup operations based on thecomponent information.

Another method is provided and includes receiving, with a systemcontroller, component identification information identifying componentsof a compressor rack and a condensing unit of a refrigeration or HVACsystem, the compressor rack having at least one compressor and anassociated rack controller and the condensing unit having at least onecondenser fan and an associated condensing unit controller. The methodalso includes retrieving, with the system controller, componentinformation including at least one of component specificationinformation, component capacity information, and component capabilityinformation, based on the component identification information. Themethod also includes performing, with the system controller, setupoperations for the refrigeration or HVAC system based on the componentinformation.

Another system is provided and includes a controller for a refrigerationor HVAC system having a compressor rack with at least one compressor anda condensing unit with at least one condenser fan, the system controllermonitoring operation of the refrigeration or HVAC system. The controllerdetermines compressor rack power consumption data corresponding to apower consumption of the compressor rack and condensing unit powerconsumption data corresponding to a power consumption of the condensingunit, determines a total power consumption of the refrigeration or HVACsystem based on the compressor rack power consumption data and thecondensing unit power consumption data, determines at least one of apredicted power consumption and a benchmark power consumption for therefrigeration system, compares the total power consumption with at leastone of the predicted power consumption and the benchmark powerconsumption, and generates a health indicator score based on thecomparison.

In other features, the controller receives performance coefficients forthe refrigeration or HVAC system and determines the predicted powerconsumption based on the performance coefficients and on operationaldata for the refrigeration or HVAC system.

In other features, the controller monitors power consumption data of therefrigeration or HVAC system over an initialization period anddetermined the benchmark power consumption based on the monitored powerconsumption data for the initialization period.

Another method is provided and includes monitoring, with a controller,operation of a refrigeration or HVAC system having a compressor rackwith at least one compressor and a condensing unit with at least onecondenser fan. The method also includes monitoring and controlling, withthe controller, operation of the compressor rack. The method alsoincludes determining, with the controller, compressor rack powerconsumption data for the compressor rack. The method also includesmonitoring and controller, with the controller, operation of thecondensing unit. The method also includes determining, with thecontroller, power consumption data for the condensing unit. The methodalso includes receiving, with the controller, the compressor rack powerconsumption data and the condensing unit power consumption data. Themethod also includes determining, with the controller, a total powerconsumption of the refrigeration or HVAC system based on the compressorrack power consumption data and the condensing unit power consumptiondata. The method also includes determining, with the controller, atleast one of a predicted power consumption and a benchmark powerconsumption for the refrigeration system. The method also includescomparing, with the controller, the total power consumption with atleast one of the predicted power consumption and the benchmark powerconsumption. The method also includes generating, with the controller, ahealth indicator score based on the comparison.

In other features, the method can also include receiving, with thecontroller, performance coefficients for the refrigeration or HVACsystem and determining, with the controller, the predicted powerconsumption based on the performance coefficients and on operationaldata for the refrigeration or HVAC system.

In other features, the method can also include monitoring, with thecontroller, power consumption data of the refrigeration or HVAC systemover an initialization period and determining, with the controller, thebenchmark power consumption based on the monitored power consumptiondata for the initialization period.

Another system is provided and includes a system controller for arefrigeration or HVAC system having a compressor rack with at least onecompressor and a condensing unit with at least one condenser fan, thesystem controller monitoring operation of the refrigeration or HVACsystem. The system also includes a rack controller in communication withthe system controller, the rack controller monitoring and controllingoperation of the compressor rack and determining compressor rack powerconsumption data. The system also includes a condensing unit controllerin communication with the system controller, the condensing unitcontroller monitoring and controlling operation of the condensing unitand determining condensing unit power consumption data. The systemcontroller monitors operational data of the HVAC system, including atleast one of a temperature and a pressure of the HVAC system, andgenerates a health indicator score based on the monitored operationaldata.

In other features, the system controller monitors at least onerefrigeration case temperature, determines a trend for the at least onerefrigeration case temperature over time, and generates the healthindicator score based on the trend.

In other features, the system controller monitors at least onerefrigeration case temperature after a defrost operation and generatesthe health indicator score based on the at least one refrigeration casetemperature after the defrost operation.

In other features, the system controller monitors at least onerefrigeration case superheat temperature, determines a trend for the atleast one refrigeration case superheat temperature over time, andgenerates the health indicator score based on the trend.

In other features, the system controller monitors a suction superheattemperature, determines a trend for the suction superheat temperatureover time, and generates the health indicator score based on the trend.

In other features, the system controller monitors an ambient temperatureand a capacity of the condensing unit, determines a correlation betweenthe ambient temperature and the capacity, determines a trend for thecorrelation over time, and generates the health indicator score based onthe trend.

Another method is provided and includes monitoring, with a controller,operation of a refrigeration or HVAC system having a compressor rackwith at least one compressor and a condensing unit with at least onecondenser fan. The method also includes monitoring and controlling, withthe controller, operation of the compressor rack. The method alsoincludes determining, with the controller, compressor rack powerconsumption data for the compressor rack. The method also includesmonitoring and controller, with the controller, operation of thecondensing unit. The method also includes monitoring, with the systemcontroller, operational data of the HVAC system, including at least oneof a temperature and a pressure of the HVAC system. The method alsoincludes generating, with the system controller, a health indicatorscore based on the monitored operational data.

In other features, the system controller monitors at least onerefrigeration case temperature. The method can also include determining,with the system controller, a trend for the at least one refrigerationcase temperature over time. The system controller generates the healthindicator score based on the trend.

In other features, the system controller monitors at least onerefrigeration case temperature after a defrost operation and generatesthe health indicator score based on the at least one refrigeration casetemperature after the defrost operation.

In other features, the system controller monitors at least onerefrigeration case superheat temperature. The method can also includedetermining, with the system controller, a trend for the at least onerefrigeration case superheat temperature over time. The systemcontroller generates the health indicator score based on the trend.

In other features, the system controller monitors a suction superheattemperature. The method also includes determining, with the systemcontroller, a trend for the suction superheat temperature over time. Thesystem controller generates the health indicator score based on thetrend.

In other features, the system controller monitors an ambient temperatureand a capacity of the condensing unit. The method further includesdetermining, with the system controller, a correlation between theambient temperature and the capacity, and determining, with the systemcontroller, a trend for the correlation over time. The system controllergenerates the health indicator score based on the trend.

A system is provided and includes a controller for a refrigeration orHVAC system having a compressor rack with at least one compressor. Thecontroller includes a monitoring module and a tracking module. Themonitoring module is configured to monitor power consumption of acompressor in the compressor rack based on data received from a powermeter associated with the compressor, a supply voltage for thecompressor, or amperage of the compressor. The tracking module isconfigured to diagnose health of the compressor based on the powerconsumption of the compressor.

In other features, the monitoring module further includes a voltagedetermining module, a power factor module, and a power consumptionmodule. The voltage determining module is configured to determine thesupply voltage for the compressor based on power supplied to thecompressor rack and a number of compressors in the compressor rack. Thepower factor module is configured to adjust a power factor for thecompressor based on the supply voltage and a voltage rating of thecompressor. The power consumption module is configured to determine thepower consumption of the compressor based on the adjusted power factor,the supply voltage for the compressor, and the amperage of thecompressor.

In other features, the monitoring module further includes a powerconsumption module and an error correction module. The power consumptionmodule is configured to estimate the power consumption of eachcompressor in the compressor rack based on the amperage of thecompressor, a voltage rating of the compressor, and a power factorrating of the compressor. The error correction module is configured todetermine an error correction factor to apply to the estimated powerconsumption of each compressor such that a sum of power consumptionvalues of each compressor and other loads of the refrigeration or HVACsystem equals a measured aggregate power consumption of the compressorrack.

Another system is provided and includes a controller for a refrigerationor HVAC system having a compressor rack with at least one compressor.The controller communicates with a tracking module configured todiagnose health of a compressor in the compressor rack. In response torated performance data for the compressor being unavailable, thetracking module is configured to generate baseline data for thecompressor and to diagnose health of the compressor by comparingoperational data of the compressor to the baseline data for thecompressor. In response to the rated performance data for the compressorbeing available, the tracking module is configured to diagnose health ofthe compressor by comparing the operational data of the compressor tothe rated performance data for the compressor.

In other features, the controller includes the performance trackingmodule.

In other features, a remote controller includes the performance trackingmodule.

In other features, the tracking module includes a baseline data moduleand a monitoring module. The baseline data module is configured togenerate the baseline data for the compressor based on data receivedfrom the compressor immediately following installation of compressor.The monitoring module is configured to diagnose health of the compressorby comparing the baseline data to the operational data of the compressorobtained subsequent to developing the baseline data.

In other features, the performance tracking module includes aregression-based monitoring module configured to perform a regressionanalysis on the rated performance data and the data obtained from thecompressor during operation and to diagnose health of the compressorbased on the regression analysis.

In other features, the regression-based monitoring module includes abenchmark generating module and an analyzing module. The benchmarkgenerating module is configured to generate a benchmark polynomial and abenchmark hull. The analyzing module is configured to analyze dataobtained from the compressor during operation using the benchmarkpolynomial and the benchmark hull and to diagnose health of thecompressor based on the analysis.

In other features, the system further includes an optimizing moduleconfigured to select only statistically significant variables affectinga selected one of the rated performance data and to eliminatestatistically insignificant variables, and to optimize the benchmarkpolynomial using the selected variables.

In other features, the system further includes an outlier detectingmodule configured to detect outliers in the data obtained from thecompressor during operation and to remove outliers with largestdeviation.

In other features, the system further includes a comparing moduleconfigured to compare the benchmark polynomial and the benchmark hullwith historical benchmark polynomial and hull data and to diagnosehealth of the compressor based on the comparison.

Another system is provided and includes a controller for a refrigerationor HVAC system having a compressor rack with at least one compressor.The controller includes a discharge line temperature determining moduleand a compressor control module. The discharge line temperaturedetermining module is configured to monitor in real time a plurality ofoperating parameters of a compressor in the compressor rack duringoperation of the compressor and to determine a minimum discharge linetemperature based on the plurality of operating parameters. Thecompressor control module is configured to shut down the compressor inresponse to a discharge line temperature of the compressor being lessthan or equal to the minimum discharge line temperature for apredetermined period of time and to restart the compressor using a bumpstart method.

In other features, the minimum discharge line temperature represents adischarge line temperature corresponding to liquid refrigerant enteringthe compressor.

In other features, the compressor control module is configured to shutdown the compressor further in response to a rate of change of thedischarge line temperature being less than or equal to a predeterminedthreshold.

In other features, the plurality of operating parameters of thecompressor includes a discharge pressure, a suction pressure, and areturn gas temperature of the compressor.

In other features, the plurality of operating parameters of thecompressor includes performance data of the compressor and properties ofa refrigerant used in the compressor.

In other features, the plurality of operating parameters of thecompressor includes whether liquid injection is employed in thecompressor.

In other features, the discharge line temperature determining module isconfigured to adjust the minimum discharge line temperature in real timebased on the plurality of operating parameters.

In other features, the controller is located remotely from therefrigeration or HVAC system, receives operational data from thecompressor, and provides the minimum discharge line temperature andshutdown and restart instructions to the compressor.

Another method is provided and includes controlling, with a controller,a refrigeration or HVAC system having a compressor rack with at leastone compressor. The method further includes monitoring, with amonitoring module, power consumption of a compressor in the compressorrack based on data received from a power meter associated with thecompressor, a supply voltage for the compressor, or amperage of thecompressor. The method further includes diagnosing, with a trackingmodule, health of the compressor based on the power consumption of thecompressor.

In other features, the monitoring the power consumption of thecompressor in the compressor rack further includes determining, with avoltage determining module, the supply voltage for the compressor basedon power supplied to the compressor rack and a number of compressors inthe compressor rack; adjusting, with a power factor module, a powerfactor for the compressor based on the supply voltage and a voltagerating of the compressor; and determining, with a power consumptionmodule, the power consumption of the compressor based on the adjustedpower factor, the supply voltage for the compressor, and the amperage ofthe compressor.

In other features, the method further includes estimating, with a powerconsumption module, the power consumption of each compressor in thecompressor rack based on the amperage of the compressor, a voltagerating of the compressor, and a power factor rating of the compressor.The method further includes determining, with an error correctionmodule, an error correction factor to apply to the estimated powerconsumption of each compressor such that a sum of power consumptionvalues of each compressor and other loads of the refrigeration or HVACsystem equals a measured aggregate power consumption of the compressorrack.

Another method is provided and includes controlling, with a controller,a refrigeration or HVAC system having a compressor rack with at leastone compressor. The method further includes communicating with aperformance tracking module configured to diagnose health of acompressor in the compressor rack. The method further includes, inresponse to rated performance data for the compressor being unavailable,generating, with the performance tracking module, baseline data for thecompressor and diagnosing health of the compressor by comparingoperational data of the compressor to the baseline data for thecompressor. The method further includes, in response to the ratedperformance data for the compressor being available, diagnosing, withthe performance tracking module, health of the compressor by comparingthe operational data of the compressor to the rated performance data forthe compressor.

In other features, the method further includes generating, with abaseline data module, the baseline data for the compressor based on datareceived from the compressor immediately following installation ofcompressor. The method further includes diagnosing, with a monitoringmodule, health of the compressor by comparing the baseline data to theoperational data of the compressor obtained subsequent to developing thebaseline data.

In other features, the method further includes performing, with aregression-based monitoring module, a regression analysis on the ratedperformance data and the data obtained from the compressor duringoperation. The method further includes diagnosing, with theregression-based monitoring module, health of the compressor based onthe regression analysis.

In other features, the method further includes generating, with abenchmark generating module, a benchmark polynomial and a benchmarkhull, and analyzing, with an analyzing module, data obtained from thecompressor during operation using the benchmark polynomial and thebenchmark hull and diagnosing health of the compressor based on theanalysis.

In other features, the method further includes selecting, with anoptimizing module, only statistically significant variables affecting aselected one of the rated performance data and eliminating statisticallyinsignificant variables; and optimizing, with the optimizing module, thebenchmark polynomial using the selected variables.

In other features, the method further includes detecting, with anoutlier detecting module, outliers in the data obtained from thecompressor during operation and removing outliers with largestdeviation.

In other features, the method further includes comparing, with acomparing module, the benchmark polynomial and the benchmark hull withhistorical benchmark polynomial and hull data and diagnosing health ofthe compressor based on the comparison.

Another method is provided and includes controlling, with a controller,a refrigeration or HVAC system having a compressor rack with at leastone compressor. The method further includes monitoring, with a dischargeline temperature determining module, in real time, a plurality ofoperating parameters of a compressor in the compressor rack duringoperation of the compressor and determining a minimum discharge linetemperature based on the plurality of operating parameters. The methodfurther includes shutting down the compressor, with a compressor controlmodule, in response to a discharge line temperature of the compressorbeing less than or equal to the minimum discharge line temperature for apredetermined period of time and restarting the compressor using a bumpstart method.

In other features, the minimum discharge line temperature represents adischarge line temperature corresponding to liquid refrigerant enteringthe compressor.

In other features, the method further includes shutting down thecompressor, with the compressor control module, further in response to arate of change of the discharge line temperature being less than orequal to a predetermined threshold.

In other features, the plurality of operating parameters of thecompressor includes a discharge pressure, a suction pressure, and areturn gas temperature of the compressor.

In other features, the plurality of operating parameters of thecompressor includes performance data of the compressor and properties ofa refrigerant used in the compressor.

In other features, the plurality of operating parameters of thecompressor includes whether liquid injection is employed in thecompressor.

In other features, the method further includes adjusting, with thedischarge line temperature determining module, the minimum dischargeline temperature in real time based on the plurality of operatingparameters.

In other features, the controller is located remotely from therefrigeration or HVAC system, and the method further includes receiving,with the controller, operational data from the compressor; andproviding, with the controller, the minimum discharge line temperatureand shutdown and restart instructions to the compressor.

Further areas of applicability will become apparent from the descriptionprovided herein. The description and specific examples in this summaryare intended for purposes of illustration only and are not intended tolimit the scope of the present disclosure.

DRAWINGS

The drawings described herein are for illustrative purposes only ofselected embodiments and not all possible implementations, and are notintended to limit the scope of the present disclosure.

FIG. 1 is a block diagram of an example refrigeration system;

FIG. 2 is a flowchart of example operation in calculating a healthindicator score;

FIG. 3 is a flowchart of example operation in calculating predictedpower consumption;

FIG. 4 is a flowchart of example operation in calculating benchmarkpower consumption;

FIG. 5 is a graph showing discharge superheat correlated with suctionsuperheat and outdoor temperature;

FIG. 6 is a flowchart of example operation in detecting and addressing acompressor flood-back condition;

FIG. 7 is a flowchart of example operation in predicting needed capacitybased on forecast data;

FIG. 8 is a flowchart of example operation in performing setup operationbased on retrieved component information;

FIGS. 9A and 9B are block diagrams of an example system for monitoringpower consumption of compressors of the refrigeration system of FIG. 1;

FIG. 10 is a flowchart of an example operation in monitoring powerconsumption of compressors of the refrigeration system of FIG. 1;

FIG. 11 is a block diagram of an example system for tracking performanceof compressors of the refrigeration system of FIG. 1;

FIG. 12 is a flowchart of an example operation in tracking performanceof compressors of the refrigeration system of FIG. 1;

FIG. 13 is a block diagram of an example regression-based system fortracking performance of compressors of the refrigeration system of FIG.1;

FIG. 14 is a flowchart of an example operation in regression-basedperformance tracking of compressors of the refrigeration system of FIG.1;

FIGS. 15A-15C are block diagrams of examples of flood-back protectionsystems for compressors of the refrigeration system of FIG. 1;

FIGS. 16A-16E are flowcharts of example operations in providingflood-back protection for compressors of the refrigeration system ofFIG. 1;

FIG. 17A is a block diagram of an example compressor identificationsystem; and

FIG. 17B is a flowchart of an example operation in compressoridentification.

In the drawings, reference numbers may be reused to identify similarand/or identical elements.

DETAILED DESCRIPTION

Example embodiments will now be described more fully with reference tothe accompanying drawings.

With reference to FIG. 1, an exemplary refrigeration system 10 is shownand includes a plurality of compressors 12 piped together in acompressor rack 14 with a common suction manifold 16 and a dischargeheader 18. While FIG. 1 shows an example refrigeration system 10, theteachings of the present disclosure also apply, for example, to HVACsystems.

Each compressor 12 has an associated compressor controller 20 thatmonitors and controls operation of the compressor 12. For example, thecompressor controller 20 may monitor electric power, voltage, and/orcurrent delivered to the compressor 12 with a power sensor, a voltagesensor, and/or a current sensor. Further, the compressor controller 20may also monitor suction or discharge temperatures or pressures of thecompressor 12 with suction or discharge temperature or pressure sensors.For example, a discharge outlet of each compressor 12 can include arespective discharge temperature sensor 22. A discharge pressure sensorcan be used in addition to, or in place of, the discharge temperaturesensor 22. An input to the suction manifold 16 can include both asuction pressure sensor 24 and a suction temperature sensor 26. Further,a discharge outlet of the discharge header 18 can include an associateddischarge pressure sensor 28. A discharge temperature sensor can be usedin addition to, or in place of, the discharge pressure sensor 28. Asdescribed in further detail below, the various sensors can beimplemented for monitoring performance and diagnosing the compressors 12in the compressor rack 14.

A rack controller 30 may monitor and control operation of the compressorrack 14 via communication with each of the compressor controllers 20.For example, the rack controller 30 may instruct individual compressors12 to turn on or turn off through communication with the compressorcontrollers 20. Additionally, the rack controller 30 may instructvariable capacity compressors to increase or decrease capacity throughcommunication with the compressor controllers 20. In addition, the rackcontroller 30 may receive data indicating the electric power, voltage,and/or current delivered to each of the compressors 12 from thecompressor controllers 20. Further, the rack controller 30 may alsoreceive data indicating the suction or discharge temperatures orpressures of each of the compressors 12 from the compressor controllers20. Additionally or alternatively, the rack controller 30 maycommunicate directly with the suction or discharge temperature orpressure sensors to receive such data. Additionally, the rack controller30 may be in communication with other suction and discharge temperatureand pressure sensors, including, for example, discharge pressure sensor28, suction pressure sensor 24, and suction temperature sensor 26.

Electric power may be delivered to the compressor rack 14 from a powersupply 32 for distribution to the individual compressors 12. A rackpower sensor 34 may sense the amount of power delivered to thecompressor rack 14. A current sensor or a voltage sensor may be used inplace of or in addition to the power sensor 34. The rack controller 30may communicate with the rack power sensor 34 and monitor the amount ofpower delivered to the compressor rack 14. Alternatively, the rack powersensor 34 may be omitted and the total power delivered to the compressorrack 14 may be determined based on the power data for the powerdelivered to each of the individual compressors 12 as determined by thecompressor controllers 20.

The compressor rack 14 compresses refrigerant vapor that is delivered toa condensing unit 36 having a condenser 38 where the refrigerant vaporis liquefied at high pressure. Condenser fans 40 may enable improvedheat transfer from the condenser 38. The condensing unit 36 can includean associated ambient temperature sensor 42, a condenser temperaturesensor 44, and/or a condenser discharge pressure sensor 46. Each of thecondenser fans 40 may include a condenser fan power sensor 47 thatsenses the amount of power delivered to each of the condenser fans 40. Acurrent sensor or a voltage sensor may be used in place of or inaddition to the condenser fan power sensor 47.

A condensing unit controller 48 may monitor and control operation of thecondenser fans 40. For example, the condensing unit controller 48 mayturn on or turn off individual condenser fans 40 and/or increase ordecrease capacity of any variable speed condenser fans 40. In addition,the condensing unit controller 48 may receive data indicating theelectric power delivered to each of the condenser fans 40 throughcommunication with the condenser fan power sensors 47. Additionally, thecondensing unit controller 48 may be in communication with the othercondensing unit sensors, including, for example, the ambient temperaturesensor 42, the condenser temperature sensor 44, and the condenserdischarge pressure sensor 46.

Electric power may be delivered to the condensing unit 36 from the powersupply 32 for distribution to the individual condenser fans 40. Acondensing unit power sensor 50 may sense the amount of power deliveredto the condensing unit 36. A current sensor or a voltage sensor may beused in place of or in addition to the condensing unit power sensor 50.The condensing unit controller 48 may communicate with the condensingunit power sensor 50 and monitor the amount of power delivered to thecondensing unit 36.

The high-pressure liquid refrigerant from the condensing unit 36 may bedelivered to refrigeration cases 52. For example, refrigeration cases 52may include a group 54 of refrigeration cases 52. The refrigerationcases 52 may be refrigerated or frozen food cases at a grocery store,for example. Each refrigeration case 52 may include an evaporator 56 andan expansion valve 58 for controlling the superheat of the refrigerantand an evaporator temperature sensor 60. The refrigerant passes throughthe expansion valve 58 where a pressure drop causes the high pressureliquid refrigerant to achieve a lower pressure combination of liquid andvapor. As hot air from the refrigeration case 52 moves across theevaporator 56, the low pressure liquid turns into gas. The low pressuregas is then delivered back to the compressor rack 14, where therefrigeration cycle starts again.

A case controller 62 may monitor and control operation of theevaporators 56 and/or the expansion valves 58. For example, the casecontroller 62 may turn on or turn off evaporator fans of the evaporators54 and/or increase or decrease capacity of any variable speed evaporatorfans. The case controller 62 may be in communication with the evaporatortemperature sensor 60 and receive evaporator temperature data.

Electric power may be delivered to the group 54 of refrigeration cases52 from the power supply 32 for distribution to the individual condenserfans 40. A refrigeration case power sensor 60 may sense the amount ofpower delivered to the group 54 of refrigeration cases 52. A currentsensor or a voltage sensor may be used in place of or in addition to therefrigeration case power sensor 60. The case controller 62 maycommunicate with the refrigeration case power sensor 60 and monitor theamount of power delivered to the group 54 of refrigeration cases 52.

As discussed above, while FIG. 1 shows an example refrigeration system10, the teachings of the present disclosure also apply, for example, toHVAC systems, including, for example, air conditioning and heat pumpsystems. In the example of an HVAC system, the evaporators 56 would beinstalled in air handler units instead of in refrigeration cases 52.

A system controller 70 monitors and controls operation of the entirerefrigeration system 10 through communication with each of the rackcontroller 30, condensing unit controller 48, and the case controller62. Alternatively, the rack controller 30, condensing unit controller48, and/or case controller 62 could be omitted and the system controller70 could directly control the compressor rack 14, condensing unit 36,and/or group 54 of refrigeration cases 52. The system controller 70 canreceive the operation data of the refrigeration system 10, as sensed bythe various sensors, through communication with the rack controller 30,condensing unit controller 48, and/or case controller 62. For example,the system controller can receive data regarding the varioustemperatures and pressures of the system and regarding electric power,current, and/or voltage delivered to the various system components.Alternatively, some or all of the various sensors may be configured tocommunicate directly with the system controller 70. For example, theambient temperature sensor 42 may communicate directly with the systemcontroller 70 and provide ambient temperature data.

The system controller 70 may coordinate operation of the refrigerationsystem, for example, by increasing or decreasing capacity of varioussystem components. For example, the system controller 70 may instructthe rack controller 30 to increase or decrease capacity by activating ordeactivating a compressor 12 or by increasing or decreasing capacity ofa variable capacity compressor 12. The system controller 70 may instructthe condensing unit controller 48 to increase or decrease condensingunit capacity by activating or deactivating a condenser fan 40 or byincreasing or decreasing a speed of a variable speed condenser fan 40.The system controller 70 may instruct the case controller 62 to increaseor decrease evaporator capacity by activating or deactivating anevaporator fan of an evaporator 56 or by increasing or decreasing aspeed of a variable speed evaporator fan. The system controller 70 mayinclude a computer-readable medium, such as a volatile or non-volatilememory, to store instructions executable by a processor to carry out thefunctionality described herein to monitor and control operation of therefrigeration system 10.

The system controller 70 may be, for example, an E2 RX refrigerationcontroller available from Emerson Climate Technologies Retail Solutions,Inc. of Kennesaw, Ga. If the system is an HVAC system instead of arefrigeration system, the system controller 70 may be, for example, anE2 BX HVAC and lighting controller also available from Emerson ClimateTechnologies Retail Solutions, Inc. of Kennesaw, Ga. Further, any othertype of programmable controller that may be programmed with thefunctionality described in the present disclosure can also be used.

The system controller 70 may be in communication with a communicationdevice 72. The communication device 72 may be, for example, a desktopcomputer, a laptop, a tablet, a smartphone or other computing devicewith communication/networking capabilities. The communication device 72may communicate with the system controller 70 via a local area networkat the facility location of the refrigeration system 10. Thecommunication device 72 may also communicate with the system controller70 via a wide area network, such as the internet.

The communication device 72 may communicate with the system controller70 to receive and view operational data of the refrigeration system 10,including, for example, energy or performance data for the refrigerationsystem 10.

The system controller 70 may also communicate with a remote monitor 74via, for example, a wide area network, such as the internet, or viaphone lines, cellular, and/or satellite communication. The remotemonitor 74 may communicate with multiple system controllers 70associated with multiple refrigeration or HVAC systems. The remotemonitor 74 may also be accessible to a communication device 76, such asa desktop computer, a laptop, a tablet, a smartphone or other computingdevice with communication/networking capabilities. The communicationdevice 76 may communicate with the remote monitor 74 to receive and viewoperational data for one or more refrigeration or HVAC systems,including, for example, energy or performance data for the refrigerationor HVAC systems.

The system controller 70 can monitor the actual power consumption of therefrigeration system 10, including the compressor rack 14, thecondensing unit 36, and the refrigeration cases 52, and compare theactual power consumption of the refrigeration system 10 with a predictedpower consumption or with a benchmark power consumption for therefrigeration system 10 to determine a health indicator score for therefrigeration system 10 and/or for individual refrigeration systemcomponents. Additionally or alternatively, the system controller 70 canmonitor the temperatures and pressures of the refrigeration system 10,including the compressor rack 14, the condensing unit 36, and therefrigeration cases 52, and compare the temperatures and/or pressureswith expected temperatures and/or pressures, based, for example, onhistorical data to determine a health indicator score for therefrigeration system 10 and/or for individual refrigeration systemcomponents.

With reference to FIG. 2, a control algorithm 200 is shown forcalculating a health indicator score for the refrigeration system and/ora refrigeration system component. The control algorithm 200 may beperformed, for example, by the system controller 70 and starts at 202.At 204, the system controller 70 receives actual power consumption datafor the refrigeration system 10 and/or for a system component of therefrigeration system 10. For example, as discussed above, the systemcontroller 70 can receive power consumption data regarding thecompressor rack 14, the condensing unit 36, and the group 54 ofrefrigeration cases 52 from the rack controller 30, the condensing unitcontroller 48, and the case controller 62. At 206, the system controller70 determines predicted or benchmark power consumption for therefrigeration system 10 and/or the system component based on operationaldata for the refrigeration system 10. Further details for determiningthe predicted or benchmark power consumption are discussed below withreference to FIGS. 3 and 4.

At 208, the system controller 70 compares the predicted or benchmarkpower consumption with the actual power consumption for the systemand/or the system component. At 210, the system controller 70 determinesa health indicator score for the refrigeration system and/or the systemcomponent based on the comparison. For example, when the actual powerconsumption is relatively close to the predicted or benchmark powerconsumption, the calculated health indicator score may indicate that therefrigeration system and/or system component is performing well.Additionally, when the actual power consumption is not relatively closeto the predicted or benchmark power consumption, the calculated healthindicator score may indicate that the refrigeration system and/or systemcomponent is not performing well.

While the control algorithm 200 is shown and described in terms ofcalculating a health indicator score for the refrigeration system 10 orfor a refrigeration system component, the system controller 70 mayadditionally or alternatively calculate a health indicator scoreindividually for each of the refrigeration system components and thendetermine an overall refrigeration system health indicator score basedon the health indicator scores for the individual components. Forexample, the system controller 70 may average the individual healthindicator scores and/or perform an averaging with a weighting functionfor certain health indicator scores to determine the overall healthindicator score for the refrigeration system 10.

The health indicator scores for the refrigeration system 10 and/or therefrigeration system components may be communicated to the communicationdevice 72, remote monitor 74, and/or communication device 76 for displayto a user of the refrigeration system. For example, the communicationdevices 72, 76 may display the overall health indicator score for therefrigeration system 10 and allow a user to drill down to view theindividual health indicator scores for the individual refrigerationsystem components. Based on the health indicator scores, the user maydetermine that maintenance is needed or that particular components needto be repaired or replaced. Additionally, the system controller 70 maysend an alert once the health indicator score for the refrigerationsystem 10 and/or a refrigeration system component is below apredetermined threshold. For example, the refrigeration system 70 maysend an alert to a user via the communication devices 72, 76 to performan inspection of the refrigeration system 10 and/or refrigeration systemcomponent with the low health indicator score. Additionally, the systemcontroller 70 may modify operation of the refrigeration system 70 toavoid use of the refrigeration system component with the low healthindicator score. The control algorithm 200 ends at 212.

Further, while control algorithm 200 is shown and described in terms ofcomparing actual power consumption with predicted or benchmark powerconsumption, other operational data values may be used by the systemcontroller 70 for the comparison to determine the health indicatorscore(s). For example, the system controller may compare an actualdischarge temperature or pressure with predicted or benchmark dischargetemperatures or pressures to determine the health indicator scores. Thepredicted or benchmark discharge temperatures or pressures may becalculated based on the performance coefficients for the componentand/or based on historical operation data for the component, includingoperational data monitored and stored during an initialization period.For example, the system controller 70 may determine a compressor rackhealth indicator score for the compressor rack 14 based on a dischargetemperature or pressure of the compressor rack 14 after stabilization.The discharge temperature or pressure of the compressor rack 14 afterstabilization could be compared with a predicted or benchmark dischargetemperature or pressure. Additionally, the operational data comparisoncould be performed in conjunction with the power consumption comparisonand the health indicator score for the component could be determinedbased on both comparisons.

Additionally or alternatively, for the refrigeration cases 52, thehealth indicator score could be based on the refrigeration case'sability to hold a predetermined temperature or superheat and/or thelength of time that the refrigeration case is able to hold thepredetermined temperature or superheat. Additionally or alternatively,the health indicator score could be based on the pull down performanceof the refrigeration case 52 after a defrost operation. In such case,the health indicator score could be based on how quickly therefrigeration case 52 is able to reach a predetermined targettemperature after a defrost operation.

With reference to FIG. 3, a control algorithm 300 is shown fordetermining predicted power consumption based on performancecoefficients for system components and operational data for the system.The functionality of FIG. 3, for example, is encapsulated at 206 of FIG.2. The control algorithm 300 may be performed by the system controller70 and starts at 302. At 304, the system controller 70 receivesperformance coefficient data for the system components of therefrigeration system 10. The performance coefficients are published bysystem component manufacturers and can be used to determine expectedoperational characteristics, including predicted power consumption, fora given system component, given particular operation conditions. Forexample, the compressor manufacturer may publish performancecoefficients for a particular model of compressor. The system controller70 may, for example, access a public database of performancecoefficients at a system component manufacturer's website and determinethe particular performance coefficients for the system componentsincluded in the refrigeration system. The performance coefficients maycorrespond to a particular model of the system component. Alternatively,the performance coefficients may be determined on a per-component basisat the time of manufacture. In such case, the performance coefficientsmay correspond to a particular model and serial number for the systemcomponent. For example, the system controller 70 may query themanufacturer's database with the particular model and serial number forthe particular component to retrieve the performance coefficients.Additionally, the performance coefficients may be stored in anon-volatile memory on or with the system component itself.Alternatively, the performance coefficients may be received from a uservia the communication device 72 or from the remote monitor 74 orcommunication device 76. After receiving the performance coefficients at304, the system controller 70 proceeds to 306.

At 306, the system controller 70 receives operational data for therefrigeration system. For example, the operational data may include:discharge temperatures and/or pressures for the compressor rack 14;suction temperatures and/or pressures for the compressor rack 14;condensing temperature; condensing unit discharge temperature and/orpressure; evaporator temperatures and/or pressures; and/or outdoorambient temperatures; etc. The operational data can be indicative of theload on the refrigeration system 10 and can be used, along withperformance coefficients, to determine predicted power consumption forthe refrigeration system 10 for a particular load.

At 308, the system controller 70 calculates the predicted powerconsumption based on the performance coefficients for the systemcomponents and the operational data for the refrigeration system 10. At310, the control algorithm 300 ends.

With reference to FIG. 4, a control algorithm 400 is shown fordetermining benchmark power consumption based on system performanceduring a predetermined time period, such as an initialization period.The functionality of FIG. 4, for example, is encapsulated at 206 of FIG.2. The control algorithm 400 may be performed by the system controller70 and starts at 402. At 404, the system controller 70 receivesoperation data for the system during a predetermined initializationperiod. For example, the predetermined initialization period may be atime period, such as one or more weeks or months, just after therefrigeration system 10 is first installed or first repaired, or aftermaintenance is performed on the refrigeration system 10. The operationaldata may include: discharge temperatures and/or pressures for thecompressor rack 14; suction temperatures and/or pressures for thecompressor rack 14; condensing temperature; condensing unit dischargetemperature and/or pressure; evaporator temperatures and/or pressures;and/or outdoor ambient temperatures; etc., as well as power consumptiondata for the refrigeration system components, such as the compressorrack 14, condensing unit 36, and refrigeration cases 52.

At 406, the system controller 70 calculates benchmark power consumptiondata based on the operational data for the system over the predeterminedinitialization period. In this way, the benchmark power consumption maybe associated, for example, with the power consumed by the system afterinstallation, maintenance, or repair. As discussed above, the actualpower consumption can then be compared with the benchmark powerconsumption to determine whether refrigeration system performance hasdegraded and to what extent additional power is being consumed by therefrigeration system 10 due to deterioration. The control algorithm 400ends at 408.

Systems and methods for calculating projected energy consumption datafor a component of a refrigeration system based on ambient temperaturedata for comparison with actual energy consumption data are described inU.S. Pat. No. 8,065,886, which is incorporated herein by reference inits entirety.

The system controller 70 may monitor operational data of therefrigeration system 10 and determine when a flood-back condition isoccurring. A flood-back condition may occur, for example, when suctionsuperheat (SSH) is approaching zero degrees. As shown in FIG. 5, SSH maybe correlated to discharge superheat (DSH). The correlation between DSHand SSH may be particularly accurate for scroll type compressors, withoutside ambient temperature being only a secondary effect. As shown inFIG. 5, correlations between DSH and SSH are shown for outdoortemperatures (ODT) of one-hundred fifteen degrees Fahrenheit,ninety-five degrees Fahrenheit, seventy-five degrees Fahrenheit, andfifty-five degrees Fahrenheit. The correlation shown in FIG. 5 is anexample only and specific correlations for specific compressors may varyby compressor type, model, capacity, etc. As further shown in FIG. 5,typical SSH temperatures for exemplar refrigerant charge levels areshown. For example, as the percentage of refrigerant charge in therefrigeration system 10 decreases, SSH typically increases.

With reference to FIG. 6, a control algorithm 600 is shown fordetermining a flood-back condition and taking appropriate measures. Thecontrol algorithm 600 may be performed by the system controller 70 andstarts at 602. At 604, the system controller 70 monitors operationaldata and calculates a discharge temperature of the compressor rack 14that corresponds to a zero degree SSH, i.e., a flood-back condition. At606, once a flood-back condition is detected, the system controller 70may notify the rack controller 30 and/or the individual compressorcontrollers 20 of the flood-back condition and instruct them to takemeasures to address the flood-back condition. The rack controller 30and/or the individual compressor controllers 20 may then takeappropriate action to address the flood-back condition. For example, therack controller 30 and/or the individual compressor controllers mayoperate any crank case heaters associated with the compressor to heatthe crankcase(s) of the compressor(s) 12 and drive liquid refrigerantout of the compressors 12. Crankcase heater systems and methods forvariable speed compressors are described, for example, in U.S. Pat. No.8,734,125, which is incorporated herein by reference in its entirety.

Additionally or alternatively, the compressor rack controller 30 and/orthe individual compressor controllers 20 may implement a flooded startcontrol algorithm for starting the individual compressors when aflood-back condition is present. For example, when started in aflood-back condition, the compressors may be cycled on and off with oneor more short on/off cycles to gradually pump liquid from the compressorwithout completely emptying the compressor of liquid refrigerant andlubricant. As more time is allowed for the refrigerant/lubricant to workthrough the refrigeration system and return to the compressor before thecompressor is emptied of liquid and lubricant. Further, the gradualpumping allows additional time for the compressor to heat up on its owndue to operation of the electric motor in the compressor and due to therotation of the internal moving parts of the compressor. Systems andmethods for flooded start control are described in U.S. Pub. No.2014/0308138, which is incorporated herein by reference in its entirety.Additionally, further, systems and methods for monitoring compressorflood-back are described in U.S. Pat. No. 9,057,549, which is likewiseincorporated herein by reference in its entirety. The control algorithm600 ends at 608.

With reference to FIG. 7, a control algorithm 700 is shown forpredicting a performance or capacity issue for a future time period. Thecontrol algorithm 700 may be performed by the system controller 70 andstarts at 702. At 704, the system controller 70 receives weather ortemperature forecast data for a future time period. The systemcontroller 70 may access a weather database or weather service websiteand/or receive weather forecast and temperature data from the remotemonitor 74, the communication device, or the communication device 76. At706, the system controller 70 estimates the predicted refrigerationcapacity that will be needed based on the indicated weather ortemperature forecast data. Based on monitoring the operational data ofthe refrigeration system 70 over time, the system controller 70 maylearn the capacity and capability of the refrigeration system 70 forvarious ambient outdoor temperatures. Based on that historical data, thesystem controller 70 may then be able to predict the refrigerationcapacity that will be needed from the refrigeration system 70 for agiven forecasted temperature. For example, based on the forecast, thesystem controller 70 can predict the anticipated load on therefrigeration system 10 as well as the anticipated refrigerationcapacity that will be needed.

At 710, the system controller 70 determines whether the predictedcapacity needed is greater than a predetermined threshold. At 710, whenthe predicted capacity needed is greater than the predeterminedthreshold, the system controller 70 can send an alert to a user oroperator of the refrigeration system 10 via the communication device 72,remote monitor 74, and/or communication device 76. Additionally, thesystem controller 70 can modify operation of the system components andschedules. For example, the system controller 70 may reschedulepreviously scheduled defrost operations. Additionally, the systemcontroller 70 may implement precooling prior to the future time period.For example, the system controller 70 may increase capacity of therefrigeration system 10 prior to the future time period to decrease thetemperature in particular refrigeration cases 52 prior to the futuretime period. In this way, the load on the refrigeration system 10 duringthe future time period may be decreased as compared with normaloperation. The control algorithm 700 ends at 712.

With reference to FIG. 8, a control algorithm 800 is shown forperforming automatic setup operations for system components based onretrieved component information. The control algorithm 800 may beperformed by the system controller 70 and/or by a specific componentcontroller, such as the rack controller 30, the condensing unitcontroller 48, and/or the case controller 62. In the example of FIG. 8,the control algorithm 800 will be discussed in terms of being performedby the rack controller 30. The control algorithm starts at 802.

At 804, the rack controller 30 determines component identificationinformation for each of the components in the compressor rack 14. Forexample, the compressor rack 14 may determine a model and serial numberfor each compressor 12 in the compressor rack 14. For example, thecompressor rack controller 30 may communicate with the compressorcontrollers 20 and retrieve model and serial number information storedat the compressor controllers 20 for the individual compressors 12.Alternatively, the compressors 12 may include a barcode that uniquelyidentifies the compressor and/or that corresponds to the compressor'smodel and serial number. An installer may scan the barcode on thecompressor with a scanning device, such as a smartphone, to obtain theunique identification information. The identification information maythen input to the rack controller and/or input to the system controller70, for example, via the communication device 72.

At 806, once the unique identification information for the compressorshas been retrieved, the rack controller 30 can retrieve componentspecification/capacity/capability information, based on theidentification information, for each component. For example, the rackcontroller 30 may access a component manufacturer website or database toretrieve information about the specific components. For example, therack controller 30 may access the compressor manufacturer's website ordatabase and retrieve information about each of the specific compressors12 in the compressor rack 14. Alternatively, the rack controller 30 maycommunicate with the system controller 70 and request the systemcontroller 70 to access the component manufacturer's website or databaseto retrieve the information.

The specification, capacity, and/or capability information may includespecific information about the particular component, such as thespecific compressors 12. For example, the specific information mayinclude: the capacity, size, and/or horsepower rating for thecompressor; the type of compressor (i.e., scroll, reciprocating, etc.);information indicating whether the compressor is a variable capacitycompressor and, if so, the type of capacity modulation available (i.e.,variable speed, blocked suction, scroll separation, etc.); informationindicating whether the compressor has an unloader device; informationindicating whether the compressor has a crankcase heater; and any otherinformation specific to the compressor that could be used by the rackcontroller 30 during operation of the compressor rack 14.

At 808, the rack controller 30 may perform setup operations based on theretrieved component specification, capacity, and capability information.For example, the rack controller 30 may store the information for eachcompressor in memory for use during operation. Additionally, the rackcontroller 30 may perform a physical to logical mapping based on theidentification information. For example, the rack controller 30 mayidentify one of the compressors as “compressor #1” in the rack and willassociate all of that compressor's specification information to thelogical “compressor #1.” At 810, the control algorithm 800 ends.

The various aspects of the present disclosure described above are nowdescribed in further detail below. The disclosure below is organized asfollows. FIGS. 9A, 9B, and 10 illustrate power monitoring of individualcompressors 12 in the compressor rack 14 shown in FIG. 1. FIGS. 11 and12 illustrate systems and methods for tracking performance of individualcompressors 12. FIGS. 13 and 14 illustrate a system and method forregression-based monitoring of compressor performance. FIGS. 15A-16Eillustrate systems and methods for providing steady-state liquidflood-back protection in compressors. FIGS. 17A and 17B illustrate asystem and method for compressor identification useful in controllingand diagnosing a compressor.

With reference to FIGS. 9A and 9B, an example of a system 900 formonitoring power consumption of individual compressors 12 in thecompressor rack 14 of FIG. 1 is shown. In FIG. 9A, the system 900 isimplemented in the system controller 70 shown in FIG. 1. The systemcontroller 70 includes a power monitoring module 902 and a performancetracking module 904. The power monitoring module 902 monitors the powerconsumption of individual compressors 12 in the compressor rack 14. Theperformance tracking module 904 tracks the performance of the individualcompressors 12 based on the power consumption monitored by the powermonitoring module 902. The performance tracking module 904 alsodiagnoses the health of the individual compressors 12 based on the powerconsumption monitored by the power monitoring module 902 and theperformance tracked by the performance tracking module 904. Accordingly,the power monitoring and performance tracking can be used for bothenergy management and maintenance and diagnostics of the refrigerationsystem 10.

As used herein, diagnosing health of a component of the refrigerationsystem such as a compressor includes the following: detecting an actualand/or probable malfunction of the component; determining whether theoperation of the component conforms to one or more manufacturer'sratings for the component; detecting and/or determining a faultcondition associated with the component; predicting and/or estimatingany of the above; predicting and/or estimating fault-free operationalduration (useful life) for the component; and providing tangibleindications or alerts regarding the above.

In FIG. 9B, an example of the power monitoring module 902 is shown. Thepower monitoring module 902 includes a power consumption module 906, avoltage determining module 908, a power factor module 910, and an errorcorrection module 912. The power consumption module 906 determines thepower consumption of each compressor 12 in different ways depending onthe type of data available. For example, if each compressor 12 has apower meter associated with it, the power consumption module 906determines the power consumption of each compressor 12 directly from thepower consumption data received from the power meter associated with therespective compressor 12. If, however, a power meter is not availablefor each compressor 12, the power consumption module 906 determines thepower consumption of each compressor 12 in one of two ways.

In a first way, the voltage determining module 908 determines a supplyvoltage available for each compressor 12 based on the power supplied tothe compressor rack 14 by the power supply 32 (shown in FIG. 1) and anumber of compressors 12 in the compressor rack 14. The power factormodule 910 adjusts a power factor for a particular compressor 12 basedon the supply voltage for the particular compressor 12 determined by thevoltage determining module 908. The power factor for the particularcompressor 12 changes due to changes in operating conditions (e.g.,load) of the particular compressor 12 and changes in the supply voltagefor the particular compressor 12. The power factor module 910 adjuststhe power factor for the particular compressor 12 to compensate fordifferences between the actual supply voltage for the particularcompressor 12 (e.g., 240V or 220V) and a voltage rating of theparticular compressor 12 (e.g., 230V).

The power factor module 910 adjusts the power factor for the particularcompressor 12 using the formula (or other PF correction formulaapplicable to the compressor)PF=Volts_(rating)*PF_(rating)*(Amps_(nominal-rating)/Amps_(actual))/Volts_(actual),where Volts_(rating) denotes the voltage rating of the particularcompressor 12, PF_(rating) denotes a power factor rating of theparticular compressor 12, Amps_(nominal-rating) denotes an amperage or acurrent rating of the particular compressor 12, Amps_(actual) denotes anactual current consumption of the particular compressor 12, andVolts_(actual) denotes the actual supply voltage for the particularcompressor 12 determined by the voltage determining module 908.

The power consumption module 906 determines the power consumption of theparticular compressor 12 based on the adjusted or corrected power factordetermined by the power factor module 910. The power consumption module906 determines the power consumption of the particular 3-phase (forexample) compressor 12 using the formula Power=Volts*PF*amps*3̂0.5, whereVolts denotes the actual supply voltage for the particular compressor 12determined by the voltage determining module 908, PF denotes theadjusted or corrected power factor determined by the power factor module910, and amps denotes the actual amperage of the particular compressor12.

In a second way, the error correction module 912 determines an errorcorrection factor in the event that the supply voltage for theparticular compressor 12 is unknown but the total power consumption ofthe compressor rack 14 is known (e.g., from the rack power sensor 34shown in FIG. 1). The power consumption of each individual compressor 12is calculated based on the actual amperage, rated voltage, and ratedpower factor of each compressor 12. The correction factor is applied tothe individual power consumption values of each compressor 12 such thatthe sum of the power consumption values of the individual compressors(plus fans and other loads) equals the measured total power consumptionof the compressor rack 14.

With reference to FIG. 10, an example of a control algorithm 1000 formonitoring power consumption of individual compressors 12 in thecompressor rack 14 is shown. For example, the control algorithm 1000 maybe performed by the system controller 70 shown in FIG. 1. The controlalgorithm 1000 starts at 1002. At 1004, the system controller 70determines whether power consumption data for a particular compressor 12is available from a power meter is associated with the particularcompressor 12. If power consumption data is available from a powermeter, the system controller 70 uses the power consumption data from thepower meter to determine the power consumption of the particularcompressor 12 at 1006.

If, however, power consumption data is unavailable from a power meter,at 1008, the system controller 70 determines whether a supply voltagefor the particular compressor 12 is available. For example, the systemcontroller 70 may determine the supply voltage for a particularcompressor 12 based on the power supplied by the power supply 32 to thecompressor rack 14 and the number of compressors 12 in the compressorrack 14 (see FIG. 1).

If the system controller 70 can determine the supply voltage for theparticular compressor 12, at 1010, the system controller 70 adjusts orcorrects a power factor for the particular compressor 12 based on thesupply voltage to compensate for difference between the actual supplyvoltage for the particular compressor 12 and a voltage rating of theparticular compressor 12. For example, the system controller 70 adjustsor corrects the power factor for the particular compressor 12 using theformula disclosed above in the description of the power factor module910 with reference to FIGS. 9A and 9B. At 1012, the system controller 70determines the power consumption of the particular compressor 12 basedon the adjusted or corrected power factor and actual supply voltage andamperage of the particular compressor 12. For example, the systemcontroller 70 determines the power consumption of the particularcompressor 12 using the formula disclosed above in the description ofthe power consumption module 906 with reference to FIGS. 9A and 9B.

If the supply voltage for the particular compressor 12 is unavailable,at 1014, the system controller 70 estimates the power consumption of theparticular compressor 12 using the amperage of the particular compressor12 and the voltage rating and the rated power factor of the particularcompressor 12. If a power meter (e.g., the rack power sensor 34 shown inFIG. 1) measures an aggregate power consumption of the compressor rack14, an error correction factor is applied such that sum of powerconsumption of individual compressors (plus fans and other loads) equalsaggregate power consumption.

At 1016, the system controller 70 uses the power consumption determinedas described above to track the performance and diagnose the health ofthe particular compressor 12. The system controller 70 determines thepower consumption of each of the compressors 12 and tracks theperformance and diagnoses the health of each of the compressors 12 asdescribed above. The control algorithm 1000 ends at 1018.

With reference to FIG. 11, an example of a system 1100 for trackingperformance of the compressors 12 in the compressor rack 14 of FIG. 1 isshown. The system 1100 can be generally implemented in the systemcontroller 70 shown in FIG. 1 and can be specifically implemented in theperformance tracking module 904 shown in FIGS. 9A and 9B. Theperformance tracking module 904 determines whether the performance ofthe compressors 12 conforms to the manufacturer's rated performance. Theperformance tracking module 904 includes a baseline data module 1102, aperformance monitoring module 1104, and a regression-based monitoringmodule (regression module) 1108. The operation of these modules isexplained below in brief with reference to FIG. 12.

Briefly, if rated performance data for the compressor 12 is unavailable,the performance tracking module 904 generates baseline data for thecompressor 12 and assesses the performance and diagnoses the health ofthe compressor 12 by comparing operational data of the compressor 12 tothe baseline data for the compressor 12. If, however, the ratedperformance data for the compressor 12 is available, the performancetracking module 904 assesses the performance and diagnoses the health ofthe compressor 12 by comparing the operational data of the compressor 12to the rated performance data for the compressor 12.

The baseline data module 1102 generates the baseline data for thecompressor 12 based on data received from the compressor 12 immediatelyfollowing installation of compressor 12. The performance monitoringmodule 1104 assesses the performance and diagnoses the health of thecompressor 12 by comparing the baseline data to the operational data ofthe compressor 12 obtained subsequent to developing the baseline datafor the compressor 12.

The regression-based monitoring module 1108 performs a regressionanalysis on the rated performance data and the data obtained from thecompressor 12 during operation and assesses the performance anddiagnoses the health of the compressor 12 based on the regressionanalysis.

With reference to FIG. 12, an example of a control algorithm 1200 fortracking performance of the compressors 12 and the compressor rack 14 ofFIG. 1 is shown. For example, the control algorithm 1200 may beperformed generally by the system controller 70 shown in FIG. 1 andspecifically by the performance tracking module 904 shown in FIG. 11.The control algorithm 1200 is explained below in brief. A detaileddescription of the modules of FIG. 11 and the control algorithm 1200follows thereafter.

The control algorithm 1200 starts at 1202. At 1204, the performancetracking module 904 determines whether rated performance data for thecompressors 12 is available. If the rated performance data for thecompressors 12 is unavailable, the baseline data module 1102 generatesbaseline data for each compressor 12 at startup following installationat 1206. At 1208, the performance monitoring module 1104 uses thebaseline data generated by the baseline data module 1102 as referenceand compares data obtained during operation with the baseline data tomonitor and assess the performance and to diagnose the health of thecompressor 12.

If, however, the rated performance data for the compressors 12 isavailable, at 1210, the performance tracking module 904 determineswhether other methods including but not limited to regression-basedanalysis is used to monitor and assess the performance and diagnose thehealth of the compressor 12. If regression-based analysis is used, at1216, the regression module 1108 uses statistically based procedures tocompare ratings and baseline data to monitored data in order to assesscompressor and system behavior and health. The control algorithm 1200ends at 1218.

With reference to FIG. 13, an example of the regression-based monitoringmodule 1108 is shown in further detail. The regression-based monitoringmodule 1108 can monitor performance of compressor, condenser,evaporator, or any other system component for which performance data isavailable. Therefore, while the operation of the regression-basedmonitoring module 1108 is described below with reference to thecompressor 12 for example only, the teachings of the present disclosurecan also be applied to monitor the performance and diagnose health ofother system components.

The regression-based monitoring module 1108 includes a benchmarkgenerating module 1900, an analyzing module 1902, an optimizing module1904, an outlier detecting module 1906, and a comparing module 1908. Theoperation of these modules is described below in detail with referenceto FIG. 14.

Briefly, the regression-based monitoring module 1108 performs aregression analysis on the rated performance data and the data obtainedfrom the compressor 12 during operation, and assesses the performanceand diagnoses the health of the compressor 12 based on the regressionanalysis as follows. The benchmark generating module 1900 generates abenchmark polynomial and a benchmark hull. The analyzing module 1902analyzes data obtained from the compressor 12 during operation using thebenchmark polynomial and the benchmark hull and assesses the performanceand diagnoses the health of the compressor 12 based on the analysis.

The optimizing module 1904 selects only statistically significantvariables affecting a selected one of the rated performance data (e.g.,power consumption of the compressor 12) and eliminates statisticallyinsignificant variables that do not significantly affect the selectedone of the rated performance data (e.g., power consumption of thecompressor 12). The optimizing module 1904 optimizes the benchmarkpolynomial using the selected variables.

The outlier detecting module 1906 detects outliers in the data obtainedfrom the compressor 12 during operation and removes outliers withlargest deviation. The comparing module 1908 compares the benchmarkpolynomial and the benchmark hull with historical benchmark polynomialand hull data and assesses the performance and diagnoses the health ofthe compressor 12 based on the comparison.

In general, the regression-based monitoring module 1108 performs thefollowing functions: data collecting and evaluation at regular intervals(e.g., multiple times a day), periodically (e.g., weekly or monthly)benchmarking and evaluation of data outside hull (explained below), andlong-term evaluation (e.g., quarterly, semiannually, or yearly). Thebenchmarking function further includes creating a model, checking themodel for validity, eliminating outliers, simplifying the model byeliminating irrelevant variables, and calculating Hull. These functionsare explained below in detail.

With reference to FIG. 14, an example of a control algorithm 2000 forregression-based performance monitoring of individual compressors 12 inthe compressor rack 14 is shown. For example, the control algorithm 2000may be performed generally by the system controller 70 shown in FIG. 1,specifically by the performance tracking module 904 shown in FIG. 11,and more specifically by the regression-based monitoring module 1108shown in FIG. 13. The control algorithm 2000 starts at 2002.

At 2004, the regression-based monitoring module 1108 collects system orcompressor sensor data multiple times a day (e.g., every second, minute,hour). For example, the data may be for power consumption, mass flowrate, or any other parameter of any system component relevant fordetermining system performance and diagnosing system health trends.

At 2006, the benchmark generating module 1900 processes the data havingrating curves and within acceptable tolerance of the rating curves. Ifthe data is not within the acceptable tolerance of the rating curves anerror or warning is generated. The data within the acceptable toleranceis stored and processed for generating benchmark polynomial andbenchmark hull. Hull is a region of data points inside of which aregression formula such as a polynomial can be used for prediction. Thebenchmark generating module 1900 generates a model and checks thevalidity of the model using statistical methods.

At 2008, the optimizing module 1904 selects only statisticallysignificant variables that affect the selected performance parameter(e.g., power consumption of the compressor 12) and eliminatesstatistically irrelevant variables to simplify the benchmark polynomialbeing generated. Additionally, the outlier detecting module 1906 detectsany outliers in the data, determines whether the outliers are not noise,and removes the outliers with the largest deviation to further simplifythe benchmark polynomial being generated. The outlier removal alsoimproves the accuracy of the model. The outliers are stored in adatabase and are evaluated over the long-term to determine whether theoutliers were caused in fact by a system problem. The optimizing module1904 optimizes the benchmark polynomial based on the selected variablesand the eliminated outliers. The optimizing module 1904 also calculatesbenchmark hull along with the benchmark polynomial for data evaluation.

At 2010, the analyzing module 1902 analyzes the system data beingcollected at regular intervals using the benchmark polynomial, thebenchmark hull, and the rating curves, and detects errors based on theanalysis. For example, the analyzing module 1902 compares the data tothe benchmark polynomial and determines whether the data is within oneor more (e.g., ±2) standard deviations of the benchmark polynomial. Theanalyzing module 1902 also determines whether the data is outside thebenchmark hull. Further, the analyzing module 1902 determines whetherthe data is within an acceptable tolerance of the rating curves for thedata. If the data is within the acceptable tolerance of the ratingcurves for the data, the data is stored and used for generating futurebenchmark polynomial and benchmark hull. If the data is not within theacceptable tolerance of the rating curves for the data, an error orwarning regarding compressor performance and health is issued.

At 2012, the comparing module 1908 periodically (e.g., quarterly,semiannually, or yearly) compares the benchmarks to detect long-termtrends, determines whether the long-term trends show any deteriorationof the equipment, and issues an error or warning if the long-term trendsshow any deterioration of the equipment.

With reference to FIGS. 15A-16E, the following portion of the presentdisclosure relates to systems and methods for providing steady-stateliquid flood-back protection in compressors (e.g., the compressors 12 inthe compressor rack 14 shown in FIG. 1). Unintentional introduction ofliquid refrigerant into a compressor can significantly degrade thereliability of the compressor. Determination of a likelihood of havingliquid refrigerant in the suction gas of a compressor (flood-back) isdone by determining a degree of superheat in the suction gas, or byusing a discharge gas temperature to determine the suction gascondition. The suction superheat method does not easily portray thequality of the return gas if the value is less than 1, whereas thedischarge temperature method can provide some insight into the degree ofseverity of the flooding condition. Knowing a relative rate of liquidrefrigerant return is important for determining an appropriate course ofaction in order to protect the compressor.

Continuous flooding at a low rate may eventually lead to reduced oilviscosity and associated bearing lubrication issues, ring wear or otherlubrication-type failures, but the response time to protect against thisproblem is relatively long. A higher rate of liquid ingestion (lowerquality refrigerant) increases the risk of damage due to lubricationissues but also (and perhaps more importantly) due to the increased riskof damage from high pressures associated with the compression of liquid.The present disclosure uses the discharge temperature to determine thesuction superheat, and can also define the quality of the return gas ifit is less than 1.

The present disclosure also includes provisions for protecting thecompressor by turning it off and re-starting with a bump-start routine.Bump start is an optional feature which provides additional floodedstart protection. Bump start drives refrigerant out of the oil,preventing the refrigerant from circulating through the compressor as aliquid and washing the oil film off of the load-bearing surfaces. Whenbump start is enabled, the compressor is turned on for a few seconds(e.g., 2 seconds), then turned off for a few seconds (e.g., 5 seconds),and this process is repeated a few times (e.g., 3 times) before thecompressor runs normally. This process allows refrigerant to exit thecompressor without the oil being removed. An example of a bump-startsystem and method is described in detail in U.S. Pat. No. 9,194,393issued on Nov. 24, 2015 assigned to Emerson Climate Technologies, Inc.,which is incorporated herein by reference in its entirety.

The following terms are used in the flood-back protection aspect of thepresent disclosure.

Quality—Mass ratio of gaseous refrigerant to the total (gas+liquidrefrigerant) in the return (suction) fluid to a compressor. Quality of1=no liquid refrigerant.

Slug—A quantity of liquid that is generally moving with the suction gasflow in the suction line of a compressor, ultimately entering thecompressor. A “slug” generally refers to a condition whereby the bulkdensity of the suction flow is rapidly increasing due to largervolumetric percentages of liquid. This event is often associated withthe termination of a defrost cycle, and is hence called a “defrostprotection” routine (although defrost termination may not be the solecause of this phenomenon).

Flood-back—A quality of suction refrigerant less than 1 (i.e., somecontinuous return of liquid). This term describes a less rapidlychanging scenario than when a compressor is “slugged”.

DLT—discharge line temperature. Ideally this is the port, head ortop-cap temperature of a compressor.

dT/dt—Rate of change of temperature with respect to time.

One embodiment of the present invention calculates a minimum allowabledischarge temperature, representing a temperature that will be developedby a compressor if the compressor is running with no superheat in thesuction gas. The design of the compressor determines whether or not“zero” superheat is a true minimum. For some compressors this may beoverly conservative, while for others this may not provide enough safetymargin. Regardless, the process can be applied for any desired returngas superheat or flood-back quality.

The inputs required to generate minimum allowable discharge temperatureinclude compressor efficiency, refrigerant properties, and operatingpressures (e.g., discharge pressure, suction pressure, and return gastemperature). The method includes consideration of factors includingwhether the compressor is operating digitally, and whether liquidinjection is being used for cooling the compressor and for modulatingthe capacity of the compressor.

One embodiment uses the remote controller 74 (shown in FIG. 1) toperform the minimum DLT calculation when the remote controller 74 hassystem operating condition information. The compressor controller 20(shown in FIG. 1) receives communication updates from the remotecontroller 74 via the system controller 70 and decides whether to shutdown the compressor 12 (shown in FIG. 1) and whether to restart thecompressor 12 using a bump start method.

In alternate embodiments, the calculation of the minimum DLT can be donein the compressor controller 20 (or in the system controller 70) ifsensor inputs and information are available. Notification of thedetection of liquid, even if it is not severe enough to warrant turningoff the compressor, can be part of the learning process to optimize thecontrols and settings for flood-back protection.

The systems and methods for providing steady-state liquid flood-backprotection according to the present disclosure include a methodologythat can be applied generically to many refrigeration compressors usingdynamic (real time) system operating conditions (pressures or saturatedtemperatures) for generation of a minimum safe operating discharge linetemperature. The temperature calculation can be adjusted dynamically (inreal time) to provide more or less safety margin based on the designconsiderations of the compressor.

FIGS. 15A-16E show examples of the systems and methods for providingsteady-state liquid flood-back protection in compressors according tothe present disclosure. FIG. 15A shows an example of implementing thesystem for providing steady-state liquid flood-back protection in thesystem controller 70 (shown in FIG. 1). FIG. 15B shows an example ofimplementing the system for providing steady-state liquid flood-backprotection in the remote controller 74 (also shown in FIG. 1). FIG. 15Cshows an example of implementing the system for providing steady-stateliquid flood-back protection in the compressor controller 20 (also shownin FIG. 1). FIGS. 16A-16E show examples of performing minimum DLTcomputation and flood-back protection.

It should be noted that the tasks of performing minimum DLT computationand flood-back protection can be partially or fully implementedindividually or in any shared manner between the system controller 70,the remote controller 74, and the compressor controller 20. For example,in some implementations, the remote controller 74 may perform theminimum DLT computation and may determine whether to shut down thecompressor 12 and whether to restart the compressor 12 using bump start.In some implementations, the remote controller 74 may directly controlthe compressor 12 (e.g., by accessing the compressor 12 via the systemcontroller 70). In some implementations, the remote controller 74 maysend the minimum DLT computation and instructions for shutting down andrestarting the compressor 12 to the system controller 70 or thecompressor controller 20, which in turn may control the compressor 12accordingly. In some implementations, the system controller 70 and orthe compressor controller 20 may perform the minimum DLT computation anddecide how to shut down and restart the compressor 12.

FIG. 16A shows an example of a method for computation of the minimum DLTin the remote controller 74 and communication of that information to thecompressor controller 20 for flood-back protection. FIG. 16B shows anexample of a control algorithm performed by the compressor controller 20for decision making regarding flood-back protection. FIG. 16C shows anexample of the inputs required for generating the minimum allowabledischarge temperature and the associated thermodynamic calculationsinvolved. FIGS. 16D and 16E show an example of an embodiment using aremote, system based controller (e.g., the remote controller 74) forcalculating the minimum DLT, and then communicating the minimum DLT tothe compressor controller 20 for decision making and flood-backprotection.

With reference to FIG. 15A, an example of a flood-back protection system2100-1 implemented in the system controller 70 is shown, where thesystem controller 70 includes a flood-back protection module 2102. Theflood-back protection module 2102 includes a DLT determining module 2104and a compressor control module 2106.

The DLT determining module 2104 monitors a plurality of operatingparameters of the compressor 12 in the compressor rack 14 duringoperation of the compressor 12. For example, the plurality of operatingparameters of the compressor 12 may include but are not limited to adischarge pressure, a suction pressure, and a return gas temperature ofthe compressor 12. For example, the DLT determining module 2104 mayreceive in real time the plurality of operating parameters from one ormore of the power monitoring module 902 and the performance trackingmodule 904, which are described above in detail with reference to FIGS.9A-14. Based on the plurality of operating parameters, the DLTdetermining module 2104 determines a minimum discharge line temperatureof the compressor 12. The DLT determining module 2104 also periodicallyupdates the minimum discharge line temperature based on the plurality ofparameters obtained in real time to adjust the minimum discharge linetemperature according to the present operating conditions of thecompressor 12.

The compressor control module 2106 determines whether to shut down thecompressor 12 by comparing a present discharge line temperature of thecompressor 12 to the minimum discharge line temperature. For example,the compressor control module 2106 may determine whether the presentdischarge line temperature of the compressor 12 is less than or equal tothe minimum discharge line temperature for a predetermined period oftime (e.g., 20 seconds). Additionally, the compressor control module2106 may determine whether a rate of change of the discharge linetemperature is less than or equal to a predetermined threshold (e.g., 0)for the predetermined period of time (e.g., 20 seconds). The compressorcontrol module 2106 may decide to shut down the compressor 12 if thepresent discharge line temperature of the compressor 12 is less than orequal to the minimum discharge line temperature and if the rate ofchange of discharge line temperature is less than or equal to thepredetermined threshold for the predetermined period of time (e.g., 20seconds). Additionally, the compressor control module 2106 determineswhether the compressor 12 should be restarted using a bump start process(e.g., see U.S. Pat. No. 9,194,393 cited above).

Further, the compressor control module 2106 may determine whether anyliquid injection is presently taking place in the compressor 12 (e.g.,for cooling the compressor 12 and/or for modulating the capacity of thecompressor 12). The compressor control module 2106 does not shut downthe compressor 12 if liquid injection is presently taking place in thecompressor 12.

With reference to FIG. 15B, an example of a flood-back protection system2100-2 implemented in the remote controller 74 is shown, where theremote controller 74 includes the flood-back protection module 2102. Theflood-back protection module 2102 includes the DLT determining module2104 and the compressor control module 2106.

The DLT determining module 2104 in the remote controller 74 receives aplurality of operating parameters of the compressor 12 in the compressorrack 14 during operation of the compressor 12. For example, the DLTdetermining module 2104 periodically receives the plurality of operatingparameters from the system controller 70 (or the compressor controller20). For example, the DLT determining module 2104 may receive theplurality of operating parameters from one or more of the powermonitoring module 902 and the performance tracking module 904, which aredescribed above in detail with reference to FIGS. 9A-14. For example,the plurality of operating parameters of the compressor 12 may includebut are not limited to a discharge pressure, a suction pressure, and areturn gas temperature of the compressor 12. Based on the plurality ofoperating parameters, the DLT determining module 2104 determines aminimum discharge line temperature of the compressor 12. The DLTdetermining module 2104 also periodically updates the minimum dischargeline temperature based on the most recently obtained plurality ofparameters from the system controller 70 (or the compressor controller20) to adjust the minimum discharge line temperature according to thepresent operating conditions of the compressor 12.

The compressor control module 2106 in the remote controller 74determines whether to shut down the compressor 12 by comparing a presentdischarge line temperature of the compressor 12 to the minimum dischargeline temperature. For example, the compressor control module 2106 maydetermine whether the present discharge line temperature of thecompressor 12 is less than or equal to the minimum discharge linetemperature for a predetermined period of time (e.g., 20 seconds).Additionally, the compressor control module 2106 may determine whether arate of change of the discharge line temperature is less than or equalto a predetermined threshold (e.g., 0) for the predetermined period oftime (e.g., 20 seconds). The compressor control module 2106 may decideto shut down the compressor 12 if the present discharge line temperatureof the compressor 12 is less than or equal to the minimum discharge linetemperature and if the rate of change of discharge line temperature isless than or equal to the predetermined threshold for the predeterminedperiod of time (e.g., 20 seconds). Additionally, the compressor controlmodule 2106 determines that the compressor 12 should be restarted usingbump start process (e.g., as described in U.S. Pat. No. 9,194,393).

Further, the compressor control module 2106 in the remote controller 74may determine whether any liquid injection is presently taking place inthe compressor 12 (e.g., for cooling the compressor 12 and/or formodulating the capacity of the compressor 12). The compressor controlmodule 2106 does not shut down the compressor 12 if liquid injection ispresently taking place in the compressor 12.

The remote controller 74 sends the minimum discharge line temperatureand data indicating whether to shut down the compressor and whether torestart the compressor 12 using bump start to the system controller 70(or the compressor controller 20) along with a date stamp, which can beused to determine the age of the minimum discharge line temperature. Thesystem controller 70 (or the compressor controller 20) controls thecompressor 12 according to the information received from the remotecontroller 74 and sends feedback to the remote controller 74 regardingthe actions performed on the compressor 12 and the status of thecompressor 12.

With reference to FIG. 15C, an example of a flood-back protection system2100-3 implemented in the compressor controller 20 is shown, where thecompressor controller 20 includes the flood-back protection module 2102.The flood-back protection module 2102 includes the DLT determiningmodule 2104 and the compressor control module 2106. The operations ofthe flood-back protection module 2102, the DLT determining module 2104,and the compressor control module 2106 are similar to those describedwith reference to FIG. 15A, except that they are performed in thecompressor controller 20 instead of in the system controller 70, and arenot repeated for brevity.

In sum, regardless of the implementation, in general, the flood-backprotection module 2102 includes the DLT determining module 2104 todetermine the minimum DLT in real time and the compressor control module2106 to determine whether to shut down the compressor 12, and if shutdown, whether to restart the compressor 12 using bump start based onfactors including whether the discharge temperature is less than theminimum DLT, whether liquid injection is taking place, and so on.

The discharge line temperature determining module 2104 monitors in realtime a plurality of operating parameters of the compressor 12 in thecompressor rack 14 during operation of the compressor 12 and determinesthe minimum discharge line temperature based on the plurality ofoperating parameters. The minimum discharge line temperature representsa discharge line temperature corresponding to liquid refrigerantentering the compressor 12. The plurality of operating parameters of thecompressor includes the discharge pressure, the suction pressure, andthe return gas temperature of the compressor 12. The plurality ofoperating parameters of the compressor 12 may also include performancedata of the compressor 12 and properties of a refrigerant used in thecompressor 12. The plurality of operating parameters of the compressor12 may further include whether liquid injection is employed in thecompressor 12. The discharge line temperature determining module 2104also adjusts the minimum discharge line temperature in real time basedon the plurality of operating parameters of the compressor 12.

The compressor control module 2106 shuts down the compressor 12 if thedischarge line temperature of the compressor 12 is less than or equal toa minimum discharge line temperature for a predetermined period of time.The compressor control module 2106 shuts down the compressor 12 byadditionally determining if the rate of change of the discharge linetemperature is less than or equal to a predetermined threshold for thepredetermined period of time. The compressor control module 2106restarts the compressor 12 using a bump start method.

With reference to FIG. 16A, an example of a control algorithm 2200-1 forcomputing the minimum discharge line temperature and performingflood-back protection from the remote controller 74 is shown. Forexample, the control algorithm 2200-1 may be performed by the remotecontroller 74 shown in FIG. 1. The control algorithm 2200-1 starts at2202.

At 2204, the remote controller 74 receives operational data of thecompressor 12 (e.g., discharge pressure, suction pressure, and returngas temperature; whether liquid injection is used; whether thecompressor 12 is digitally controlled, etc.). At 2206, the remotecontroller 74 computes the minimum DLT based on the operational data ofthe compressor 12. At 2208, the remote controller 74 determines whetherthe present discharge temperature of the compressor 12 is greater thanthe minimum DLT. The control algorithm 2200-1 returns to 2204 if thepresent discharge temperature of the compressor 12 is greater than theminimum DLT (or if liquid injection is taking place in the compressor12).

If, however, the present discharge temperature of the compressor 12 isnot greater than the minimum DLT, at 2210, the remote controller 74sends data including the minimum DLT and shut down/bump startinstructions to the compressor controller 20 (or the system controller70) along with a date stamp. At 2212, the compressor controller 20 (orthe system controller 70) shuts down the compressor 12 and restarts thecompressor 12 using a bump start procedure according to the datareceived from the remote controller 74. At 2214, the compressorcontroller 20 (or the system controller 70) sends feedback includingoperational data and bump start status of the compressor 12 to theremote controller 74. The control algorithm 2200-1 returns to 2206.

With reference to FIG. 16B, an example of a control algorithm 2200-2 forproviding flood-back protection from the compressor controller 20 isshown. For example, the control algorithm 2200-2 may be performed by thecompressor controller 20 shown in FIG. 1. The control algorithm 2200-2starts at 2220.

At 2222, the compressor controller 20 determines whether liquidinjection is taking place in the compressor 12. The control algorithm2200-2 takes no action if liquid injection is taking place in thecompressor 12. If liquid injection is not taking place in the compressor12, at 2224, the compressor controller 20 determines whether the minimumDLT data is old (e.g., older than 60 seconds). For example, the minimumDLT data may be periodically generated by the compressor controller 20,the system controller 70, or the remote controller 74. The controlalgorithm 2200-2 takes no action if the minimum DLT data is old (e.g.,older than 60 seconds). If the minimum DLT data is not old (e.g., notolder than 60 seconds), at 2226, the compressor controller 20 determineswhether the present discharge temperature of the compressor 12 isgreater than the minimum DLT. The control algorithm 2200-2 takes noaction if the present discharge temperature of the compressor 12 isgreater than the minimum DLT. If the present discharge temperature ofthe compressor 12 is not greater than the minimum DLT, at 2228, thecompressor controller 20 determines whether the rate of change ofdischarge temperature of the compressor 12 is greater than apredetermined threshold (e.g., 0). The control algorithm 2200-2 takes noaction if the rate of change of discharge temperature of the compressor12 is greater than a predetermined threshold (e.g., 0).

If the rate of change of discharge temperature of the compressor 12 isnot greater than a predetermined threshold (e.g., 0), at 2230, thecompressor controller determines if the discharge temperature is notgreater than the minimum DLT and the rate of change of dischargetemperature is not greater than the predetermined threshold for apredetermined period of time (e.g., 20 seconds). If the dischargetemperature is not greater than the minimum DLT and the rate of changeof discharge temperature is not greater than the predetermined thresholdfor a predetermined period of time (e.g., 20 seconds), at 2232, thecompressor controller 20 shuts down the compressor 12 and after apredetermined time period restarts the compressor 12 using a bump startmethod. At 2234, the compressor controller 20 communicates theoperational data and status of the compressor 12 to the remotecontroller 74 and/or the system controller 70. The control algorithm2200-2 returns to 2222.

In the predetermined period of time mentioned above with reference toflood-back protection, predetermined means an established method oralgorithm. Accordingly, the predetermined period of time mentioned abovewith reference to flood-back protection can mean a fixed time period ora time period based on a methodology such as an inverse-time algorithm,for example. The inverse time algorithm will respond quicker if thedeviation between actual DLT and minimum DLT increases in an adversedirection.

With reference to FIG. 16C, an example of a control algorithm 2200-3 forcomputing the minimum DLT is shown. For example, the control algorithm2200-3 may be performed by the compressor controller 20 (preferably),the system controller 70, or the remote controller 74 shown in FIG. 1.In the following description of the control algorithm 2200-3, the termcontroller refers to the compressor controller 20, the system controller70, or the remote controller 74 shown in FIG. 1. Further, the controlleruses various thermodynamic computations when performing the calculationsindicated. The control algorithm 2200-3 starts at 2240.

At 2242, the controller obtains the ratings data of the compressor 12(e.g., including power consumption, capacity, mass flow throughevaporator, etc.). For example, the compressor controller 20 may obtainthe ratings data from the compressor 12; the system controller 70 mayobtain the ratings data from the compressor controller 20; and theremote controller 74 may obtain the ratings data directly from thecompressor 12, the compressor controller 20, or the system controller70.

At 2244, the controller determines present values of discharge andsuction pressures of the compressor 12 (e.g., based on suctiontransducer data and refrigerant property data). At 2246, the controlleradjusts evaporator mass flow and power consumption at a targeted returngas condition using adjustment factors. At 2248, the controllerdetermines whether refrigerant injection is employed by the compressor12. If refrigerant injection is present, at 2250, the controllercalculates mass flow of refrigerant injection. At 2252, the controllercalculates the discharge temperature at the targeted return gascondition of the compressor 12. The control algorithm 2200-3 ends at2254.

With reference to FIGS. 16D and 16E, an example of a control algorithm2200-4 to calculate the minimum DLT using a remote, system basedcontroller (e.g., the remote controller 74) and to communicate theminimum DLT to the compressor controller 20 for decision making andflood-back protection is shown. For example, the control algorithm2200-4 may be performed partially by the remote controller 74 andpartially by the compressor controller 20 shown in FIG. 1. The controlalgorithm 2200-4 starts at 2260.

At 2262, the availability of the remote controller 74 is determined. Ifthe remote controller 74 is not available, at 2264, the compressorcontroller 20 receives data from the compressor 12 including thecompressor model number, the refrigerant type, etc. At 2266, thecompressor controller 20 reads evaporating and condensing temperaturesor pressures, and compressor discharge temperature. At 2268, thecompressor controller 20 calculates the minimum DLT of the compressor12. At 2270, using a flood-back algorithm, the compressor controller 20decides whether to continue to run or shut down the compressor 12; andif shut down, whether to restart the compressor 12 using a bump startmethod. The control algorithm 2200-4 ends at 2272.

If, however, the remote controller 74 is available, at 2274, the remotecontroller 74 obtains data including the compressor model number, therefrigerant type, etc. (e.g., directly from the compressor 12, thecompressor controller 20 or the system controller 70). At 2276, theremote controller 74 receives evaporating and condensing temperatures orpressures, and compressor discharge temperature (e.g., from thecompressor controller 20 and the system controller 70). At 2278, theremote controller 74 calculates the minimum DLT of the compressor 12.

At 2280, whether the remote controller 74 can directly read compressordischarge temperature from the compressor 12 is determined. If theremote controller 74 cannot directly read compressor dischargetemperature from the compressor 12, at 2282, the remote controller 74obtains the discharge temperature from the compressor controller 20.

At 2284, whether the remote controller 74 can control the compressorcontactor is determined. If the remote controller 74 can control thecompressor contactor, at 2286, if the discharge temperature is not readby the remote controller 74, the discharge temperature is communicatedto the remote controller 74 by the compressor controller 20 or by thesystem controller 70, for example. At 2288, using a flood-backalgorithm, the remote controller 74 decides whether to continue to runor shut down the compressor 12; and if shut down, whether to restart thecompressor 12 using a bump start method. The control algorithm 2200-4ends at 2290.

If, however, the remote controller 74 cannot control the compressorcontactor, at 2292, the remote controller 74 sends the dischargetemperature to the compressor controller 20. At 2294, using a flood-backalgorithm, the compressor controller 20 decides whether to continue torun or shut down the compressor 12; and if shut down, whether to restartthe compressor 12 using a bump start method. The control algorithm2200-4 ends at 2290.

With reference to FIG. 17A, an example of a system 2300 for compressoridentification implemented in the system controller 70 is shown. Thesystem controller 70 includes a receiving module 2302, and identifyingmodule 2304, a set up module 2306, a selecting module 2308, and atransmitting module 2310. Additionally, the system controller 70includes the power monitoring module 902, the performance trackingmodule 904, and the flood-back protection module 2102, which are shownand described above with reference to FIGS. 9A-16E. These modules aredescribed below in detail with reference to FIG. 17B.

Briefly, the receiving module 2302 receives identification informationof the compressor 12 in the compressor rack 14. For example, theidentifying information includes a model number and a serial number ofthe compressor 12. The identifying module 2304 determines a plurality ofoperating characteristics of the compressor 12 based on theidentification information. For example, the plurality of operatingcharacteristics of the compressor 12 includes one or more of a type ofmodulation used by the compressor 12, a type of injection used by thecompressor 12, a type of oil used by the compressor 12, one or morecharacteristics of a motor used by the compressor 12, and rating data ofthe compressor 12. The setup module 2306 configures or initializes thecompressor 12 based on the plurality of operating characteristics of thecompressor 12.

The power monitoring module 902 monitors the power consumption of thecompressor 12 based on the plurality of operating characteristics of thecompressor 12 as described above with reference to FIGS. 9A, 9B, and 10.The performance tracking module 904 tracks the performance of thecompressor 12 based on the plurality of operating characteristics of thecompressor 12 as described above with reference to FIGS. 11-14. Theflood-back protection module 2102 calculates a discharge linetemperature of the compressor 12 based on the plurality of operatingcharacteristics of the compressor and provides flood-back protection tothe compressor 12 as described above with reference to FIGS. 16A-16E.

The selecting module 2308 selects one or more controls (e.g., injectionmode) to operate the compressor 12 based on the plurality of operatingcharacteristics of the compressor 12. The transmitting module 2310 sendsone or more of the identification information and operational data ofthe compressor 12 to a remote device (e.g., the remote controller 74shown in FIG. 1). The receiving module 2302 receives data forcontrolling the compressor 12 from the remote device based on the one ormore of the identification information and the operational data of thecompressor 12 sent to the remote device. The system controller 70controls the compressor 12 based on the data received from the remotedevice. The transmitting module also sends the identificationinformation and operational data of the compressor to the remote devicefor diagnosing the compressor 12 and scheduling service for thecompressor 12 from the remote device.

With reference to FIG. 17B, an example of a control algorithm 2350 forcompressor identification is shown. For example, the control algorithm2350 may be performed by the system controller 70 shown in FIG. 17A. Thecontrol algorithm 2350 starts at 2352.

At 2354, the receiving module 2302 receives identifying information fromthe compressor 12. At 2356, the identifying module 2304 determinesoperating characteristics of the compressor 12 based on the identifyinginformation. At 2358, the setup module 2306 configures or initializesthe compressor 12 based on the operating characteristics. At 2360, theselecting module 2308 select controls (e.g., injection mode) to operatethe compressor 12 based on the operating characteristics.

At 2362, the power monitoring module 902 performs power monitoring, theperformance tracking module 904 tracks performance, and the flood-backprotection module 2102 provides flood-back protection for the compressor12 based on the operating characteristics. At 2364, the transmittingmodule 2310 sends the identifying information and/or the operatingcharacteristics of the compressor 12 to the remote controller 74. At2366, the receiving module 2302 receives data for controlling thecompressor 12 from the remote controller 74 and controls the compressor12 based on the received data. At 2368, the remote controller 74diagnoses the compressor 12 and schedules service for the compressor 12.The control algorithm 2350 ends at 2370.

In summary, the systems and methods described above provide andmaintenance and diagnostics information for refrigeration systems.Specifically, the systems and methods can provide health indicators foreach of the compressors 12 and other components of the refrigerationsystem 10 individually as well as for the entire the refrigerationsystem 10 as a whole. The systems and methods provide flood-backprediction and protection and bump start procedures for therefrigeration system 10. The systems and methods can predict aperformance issue for the refrigeration system 10 based on futureconditions. The systems and methods provide the ability to automaticallysetup the compressors 12 based on reading the compressor information.

The foregoing description is merely illustrative in nature and is in noway intended to limit the disclosure, its application, or uses. Thebroad teachings of the disclosure can be implemented in a variety offorms. Therefore, while this disclosure includes particular examples,the true scope of the disclosure should not be so limited since othermodifications will become apparent upon a study of the drawings, thespecification, and the following claims. It should be understood thatone or more steps within a method may be executed in different order (orconcurrently) without altering the principles of the present disclosure.Further, although each of the embodiments is described above as havingcertain features, any one or more of those features described withrespect to any embodiment of the disclosure can be implemented in and/orcombined with features of any of the other embodiments, even if thatcombination is not explicitly described. In other words, the describedembodiments are not mutually exclusive, and permutations of one or moreembodiments with one another remain within the scope of this disclosure.

Spatial and functional relationships between elements (for example,between modules, circuit elements, semiconductor layers, etc.) aredescribed using various terms, including “connected,” “engaged,”“coupled,” “adjacent,” “next to,” “on top of,” “above,” “below,” and“disposed.” Unless explicitly described as being “direct,” when arelationship between first and second elements is described in the abovedisclosure, that relationship can be a direct relationship where noother intervening elements are present between the first and secondelements, but can also be an indirect relationship where one or moreintervening elements are present (either spatially or functionally)between the first and second elements. As used herein, the phrase atleast one of A, B, and C should be construed to mean a logical (A OR BOR C), using a non-exclusive logical OR, and should not be construed tomean “at least one of A, at least one of B, and at least one of C.”

In the figures, the direction of an arrow, as indicated by thearrowhead, generally demonstrates the flow of information (such as dataor instructions) that is of interest to the illustration. For example,when element A and element B exchange a variety of information butinformation transmitted from element A to element B is relevant to theillustration, the arrow may point from element A to element B. Thisunidirectional arrow does not imply that no other information istransmitted from element B to element A. Further, for information sentfrom element A to element B, element B may send requests for, or receiptacknowledgements of, the information to element A.

In this application, including the definitions below, the term “module”or the term “controller” may be replaced with the term “circuit.” Theterm “module” may refer to, be part of, or include: an ApplicationSpecific Integrated Circuit (ASIC); a digital, analog, or mixedanalog/digital discrete circuit; a digital, analog, or mixedanalog/digital integrated circuit; a combinational logic circuit; afield programmable gate array (FPGA); a processor circuit (shared,dedicated, or group) that executes code; a memory circuit (shared,dedicated, or group) that stores code executed by the processor circuit;other suitable hardware components that provide the describedfunctionality; or a combination of some or all of the above, such as ina system-on-chip.

The module may include one or more interface circuits. In some examples,the interface circuits may include wired or wireless interfaces that areconnected to a local area network (LAN), the Internet, a wide areanetwork (WAN), or combinations thereof. The functionality of any givenmodule of the present disclosure may be distributed among multiplemodules that are connected via interface circuits. For example, multiplemodules may allow load balancing. In a further example, a server (alsoknown as remote, or cloud) module may accomplish some functionality onbehalf of a client module.

The term code, as used above, may include software, firmware, and/ormicrocode, and may refer to programs, routines, functions, classes, datastructures, and/or objects. The term shared processor circuitencompasses a single processor circuit that executes some or all codefrom multiple modules. The term group processor circuit encompasses aprocessor circuit that, in combination with additional processorcircuits, executes some or all code from one or more modules. Referencesto multiple processor circuits encompass multiple processor circuits ondiscrete dies, multiple processor circuits on a single die, multiplecores of a single processor circuit, multiple threads of a singleprocessor circuit, or a combination of the above. The term shared memorycircuit encompasses a single memory circuit that stores some or all codefrom multiple modules. The term group memory circuit encompasses amemory circuit that, in combination with additional memories, storessome or all code from one or more modules.

The term memory circuit is a subset of the term computer-readablemedium. The term computer-readable medium, as used herein, does notencompass transitory electrical or electromagnetic signals propagatingthrough a medium (such as on a carrier wave); the term computer-readablemedium may therefore be considered tangible and non-transitory.Non-limiting examples of a non-transitory, tangible computer-readablemedium are nonvolatile memory circuits (such as a flash memory circuit,an erasable programmable read-only memory circuit, or a mask read-onlymemory circuit), volatile memory circuits (such as a static randomaccess memory circuit or a dynamic random access memory circuit),magnetic storage media (such as an analog or digital magnetic tape or ahard disk drive), and optical storage media (such as a CD, a DVD, or aBlu-ray Disc).

The apparatuses and methods described in this application may bepartially or fully implemented by a special purpose computer created byconfiguring a general purpose computer to execute one or more particularfunctions embodied in computer programs. The functional blocks,flowchart components, and other elements described above serve assoftware specifications, which can be translated into the computerprograms by the routine work of a skilled technician or programmer.

The computer programs include processor-executable instructions that arestored on at least one non-transitory, tangible computer-readablemedium. The computer programs may also include or rely on stored data.The computer programs may encompass a basic input/output system (BIOS)that interacts with hardware of the special purpose computer, devicedrivers that interact with particular devices of the special purposecomputer, one or more operating systems, user applications, backgroundservices, background applications, etc.

The computer programs may include: (i) descriptive text to be parsed,such as HTML (hypertext markup language) or XML (extensible markuplanguage), (ii) assembly code, (iii) object code generated from sourcecode by a compiler, (iv) source code for execution by an interpreter,(v) source code for compilation and execution by a just-in-timecompiler, etc. As examples only, source code may be written using syntaxfrom languages including C, C++, C#, Objective C, Haskell, Go, SQL, R,Lisp, Java®, Fortran, Perl, Pascal, Curl, OCaml, Javascript®, HTML5,Ada, ASP (active server pages), PHP, Scala, Eiffel, Smalltalk, Erlang,Ruby, Flash®, Visual Basic®, Lua, and Python®.

None of the elements recited in the claims are intended to be ameans-plus-function element within the meaning of 35 U.S.C. § 112(f)unless an element is expressly recited using the phrase “means for,” orin the case of a method claim using the phrases “operation for” or “stepfor.”

What is claimed is:
 1. A system comprising: a controller for arefrigeration or HVAC system having a compressor rack with at least onecompressor, wherein the controller communicates with a tracking moduleconfigured to diagnose health of a compressor in the compressor rack,wherein in response to rated performance data for the compressor beingunavailable, the tracking module is configured to generate baseline datafor the compressor and to diagnose health of the compressor by comparingoperational data of the compressor to the baseline data for thecompressor; and wherein in response to the rated performance data forthe compressor being available, the tracking module is configured todiagnose health of the compressor by comparing the operational data ofthe compressor to the rated performance data for the compressor.
 2. Thesystem of claim 1 wherein the controller comprises the performancetracking module.
 3. The system of claim 1 wherein a remote controllercomprises the performance tracking module.
 4. The system of claim 1wherein the tracking module comprises: a baseline data module configuredto generate the baseline data for the compressor based on data receivedfrom the compressor immediately following installation of compressor;and a monitoring module configured to diagnose health of the compressorby comparing the baseline data to the operational data of the compressorobtained subsequent to developing the baseline data.
 5. The system ofclaim 1 wherein the performance tracking module comprises aregression-based monitoring module configured to: perform a regressionanalysis on the rated performance data and the data obtained from thecompressor during operation; and diagnose health of the compressor basedon the regression analysis.
 6. The system of claim 5 wherein theregression-based monitoring module comprises: a benchmark generatingmodule configured to generate a benchmark polynomial and a benchmarkhull; and an analyzing module configured to analyze data obtained fromthe compressor during operation using the benchmark polynomial and thebenchmark hull and to diagnose health of the compressor based on theanalysis.
 7. The system of claim 6 further comprising an optimizingmodule configured to: select only statistically significant variablesaffecting a selected one of the rated performance data and to eliminatestatistically insignificant variables; and optimize the benchmarkpolynomial using the selected variables.
 8. The system of claim 6further comprising an outlier detecting module configured to detectoutliers in the data obtained from the compressor during operation andto remove outliers with largest deviation.
 9. The system of claim 6further comprising a comparing module configured to compare thebenchmark polynomial and the benchmark hull with historical benchmarkpolynomial and hull data and to diagnose health of the compressor basedon the comparison.
 10. A method comprising: controlling, with acontroller, a refrigeration or HVAC system having a compressor rack withat least one compressor; communicating with a performance trackingmodule configured to diagnose health of a compressor in the compressorrack; in response to rated performance data for the compressor beingunavailable, generating, with the performance tracking module, baselinedata for the compressor and diagnosing health of the compressor bycomparing operational data of the compressor to the baseline data forthe compressor; and in response to the rated performance data for thecompressor being available, diagnosing, with the performance trackingmodule, health of the compressor by comparing the operational data ofthe compressor to the rated performance data for the compressor.
 11. Themethod of claim 10 further comprising: generating, with a baseline datamodule, the baseline data for the compressor based on data received fromthe compressor immediately following installation of compressor; anddiagnosing, with a monitoring module, health of the compressor bycomparing the baseline data to the operational data of the compressorobtained subsequent to developing the baseline data.
 12. The method ofclaim 10 further comprising: performing, with a regression-basedmonitoring module, a regression analysis on the rated performance dataand the data obtained from the compressor during operation; anddiagnosing, with the regression-based monitoring module, health of thecompressor based on the regression analysis.
 13. The method of claim 12further comprising: generating, with a benchmark generating module, abenchmark polynomial and a benchmark hull; and analyzing, with ananalyzing module, data obtained from the compressor during operationusing the benchmark polynomial and the benchmark hull and diagnosinghealth of the compressor based on the analysis.
 14. The method of claim13 further comprising: selecting, with an optimizing module, onlystatistically significant variables affecting a selected one of therated performance data and eliminating statistically insignificantvariables; and optimizing, with the optimizing module, the benchmarkpolynomial using the selected variables.
 15. The method of claim 13further comprising detecting, with an outlier detecting module, outliersin the data obtained from the compressor during operation and removingoutliers with largest deviation.
 16. The method of claim 13 furthercomprising comparing, with a comparing module, the benchmark polynomialand the benchmark hull with historical benchmark polynomial and hulldata and diagnosing health of the compressor based on the comparison.